Abstract: In this study, numerical simulations on laminar flow in
sinusoidal wavy shaped tubes were conducted for mean Reynolds
number of 250, which is in the range of physiological flow-rate and
investigated flow structures, pressure distribution and particle
trajectories both in steady and periodic inflow conditions. For
extensive comparisons, various wave lengths and amplitudes of sine
function for geometry of tube models were employed. The results
showed that small amplitude secondary curvature has significant
influence on the nature of flow patterns and particle mixing
mechanism. This implies that characterizing accurate geometry is
essential in accurate predicting of in vivo hemodynamics and may
motivate further study on any possibility of reflection of secondary
flow on vascular remodeling and pathophysiology.
Abstract: This paper will first describe predictor controllers
when the proportional-integral-derivative (PID) controllers are
inactive for procedures that have large delay time (LDT) in transfer
stage. Therefore in those states, the predictor controllers are better
than the PID controllers, then compares three types of predictor
controllers. The value of these controller-s parameters are obtained
by trial and error method, so here an effort has been made to obtain
these parameters by Ziegler-Nichols method. Eventually in this paper
Ziegler-Nichols method has been described and finally, a PIP
controller has been designed for a thermal system, which circulates
hot air to keep the temperature of a chamber constant.
Abstract: This paper is a part of research, in which the way the
biomedical engineers follow in their work is analyzed. The goal of
this paper is to present a method for specification of user
requirements in the medical devices maintenance process. Data
Gathering Methods, Research Model Phases and Descriptive
Analysis is presented. These technology and verification rules can be
implemented in Medical devices maintenance management process to
the maintenance process.
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: In this paper, a novel scheme is proposed for ownership identification and authentication using color images by deploying Cryptography and Digital Watermarking as underlaying technologies. The former is used to compute the contents based hash and the latter to embed the watermark. The host image that will claim to be the rightful owner is first transformed from RGB to YST color space exclusively designed for watermarking based applications. Geometrically YS ÔèÑ T and T channel corresponds to the chrominance component of color image, therefore suitable for embedding the watermark. The T channel is divided into 4×4 nonoverlapping blocks. The size of block is important for enhanced localization, security and low computation. Each block along with ownership information is then deployed by SHA160, a one way hash function to compute the content based hash, which is always unique and resistant against birthday attack instead of using MD5 that may raise the condition i.e. H(m)=H(m'). The watermark payload varies from block to block and computed by the variance factorα . The quality of watermarked images is quite high both subjectively and objectively. Our scheme is blind, computationally fast and exactly locates the tampered region.
Abstract: With the advance of information technology in the
new era the applications of Internet to access data resources has
steadily increased and huge amount of data have become accessible
in various forms. Obviously, the network providers and agencies,
look after to prevent electronic attacks that may be harmful or may
be related to terrorist applications. Thus, these have facilitated the
authorities to under take a variety of methods to protect the special
regions from harmful data. One of the most important approaches is
to use firewall in the network facilities. The main objectives of
firewalls are to stop the transfer of suspicious packets in several
ways. However because of its blind packet stopping, high process
power requirements and expensive prices some of the providers are
reluctant to use the firewall. In this paper we proposed a method to
find a discriminate function to distinguish between usual packets and
harmful ones by the statistical processing on the network router logs.
By discriminating these data, an administrator may take an approach
action against the user. This method is very fast and can be used
simply in adjacent with the Internet routers.
Abstract: The present paper aims to present the significant role that the concept of governance can play in order to combine naturals resources as useful funding basis for the formation of a stable and effective welfare state model. The combination of those two different fields aims to represent the modern trends of our era as the means to solve the severe financial and economic issues caused mostly due to the malfunction of the welfare state and its public sector. European Union and Asian countries (especially China) are the main areas of interest since EU experiences a fiscal and economic crisis while China rules the area of the natural resources exploiting 97% of rare earths elements worldwide.
Abstract: In the proposed method for Web page-ranking, a
novel theoretic model is introduced and tested by examples of order
relationships among IP addresses. Ranking is induced using a
convexity feature, which is learned according to these examples
using a self-organizing procedure. We consider the problem of selforganizing
learning from IP data to be represented by a semi-random
convex polygon procedure, in which the vertices correspond to IP
addresses. Based on recent developments in our regularization
theory for convex polygons and corresponding Euclidean distance
based methods for classification, we develop an algorithmic
framework for learning ranking functions based on a Computational
Geometric Theory. We show that our algorithm is generic, and
present experimental results explaining the potential of our approach.
In addition, we explain the generality of our approach by showing its
possible use as a visualization tool for data obtained from diverse
domains, such as Public Administration and Education.
Abstract: Fruits and vegetables are the essentials of a healthy
diet, mainly because of their antioxidant properties contributing to
disease blockage especially for some certain types of cancer. Being a
favourite fruit, citrus are produced for economic and commercial
purposes worldwide. Particularly, lemon fruit (Citrus limon L.), has
an important place in export products of Turkey. Lemon has a great
importance on human nutrition with regard to being a source of
nutrients, flavonoids, vitamin C and minerals. It is used for food
flavouring and pickling and also processed for lemonade. By
processing citrus into fruit juices, consumption may increase and also
become easier. Like many fruits and vegetables lemons are cheap and
abundant during harvesting period, while they are quite expensive in
other seasons. Lemon juice and concentrate production allows
consumers to get benefits from lemon fruit in any time of the year.
Lemonade is getting in to the focus of consumers’ attention
preferring non-carbonated drinks. The demand of healthy, convenient
functional foods affects consumer trends through innovative
products. For this reason, lemonade could be enriched with different
natural herb extracts such as ginger (Zingiber officinale), linden (Tilia
cordata), and mint (Mentha piperita).
Abstract: The curriculum of the primary school science course was redesigned on the basis of constructivism in 2005-2006 academic years, in Turkey. In this context, the name of this course has been changed as “Science and Technology"; and both content and course books, students workbooks for this course have been redesigned in light of constructivism. The aim of this study is to determine whether the Science and Technology course books and student work books for primary school 5th grade are appropriate for the constructivism by evaluating them in terms of the fundamental principles of constructivism. In this study, out of qualitative research methods, documentation technique (i.e. document analysis) is applied; while selecting samples, criterion-sampling is used out of purposeful sampling techniques. When the Science and Technology course book and workbook for the 5th grade in primary education are examined, it is seen that both books complete each other in certain areas. Consequently, it can be claimed that in spite of some inadequate and missing points in the course book and workbook of the primary school Science and Technology course for the 5th grade students, these books are attempted to be designed in terms of the principles of constructivism. To overcome the inadequacies in the books, it can be suggested to redesign them. In addition to them, not to ignore the technology dimension of the course, the activities that encourage the students to prepare projects using technology cycle should be included.
Abstract: Developing an accurate classifier for high dimensional microarray datasets is a challenging task due to availability of small sample size. Therefore, it is important to determine a set of relevant genes that classify the data well. Traditionally, gene selection method often selects the top ranked genes according to their discriminatory power. Often these genes are correlated with each other resulting in redundancy. In this paper, we have proposed a hybrid method using feature ranking and wrapper method (Genetic Algorithm with multiclass SVM) to identify a set of relevant genes that classify the data more accurately. A new fitness function for genetic algorithm is defined that focuses on selecting the smallest set of genes that provides maximum accuracy. Experiments have been carried on four well-known datasets1. The proposed method provides better results in comparison to the results found in the literature in terms of both classification accuracy and number of genes selected.
Abstract: This paper reports our analysis of 163 ks observations
of PSR J0538+2817 with the Rossi X-Ray Timing Explorer
(RXTE).The pulse profiles, detected up to 60 keV, show a single
peak asin the case for radio frequency. The profile is well described
by one Gaussians function with full width at half maximum (FWHM)
0.04794. We compared the difference of arrival time between radio
and X-ray pulse profiles for the first time. It turns out that the phase
of radio emits precede the X-ray by 8.7 ± 4.5 ms. Furthermore we
obtained the pulse profiles in the energy ranges of 2.29-6.18 keV,
6.18-12.63 keV and 12.63-17.36 keV. The intensity of pulses
decreases with the increasing energy range. We discuss the emission
geometry in our work.
Abstract: This work will provide a new perspective of exploring innovation thematic. It will reveal that radical and incremental innovations are complementary during the innovation life cycle and accomplished through distinct ways of developing new products. Each new product development process will be constructed according to the nature of each innovation and the state of the product development. This paper proposes the inclusion of the organizational function areas that influence new product's development on the new product development process.
Abstract: Chemical and physical functionalization of multiwalled
carbon nanotubes (MWCNT) has been commonly practiced to
achieve better dispersion of carbon nanotubes (CNTs) in polymer
matrix. This work describes various functionalization methods (acidtreatment,
non-ionic surfactant treatment with TritonX-100),
fabrication of MWCNT/PP nanocomposites via melt blending and
characterization of mechanical properties. Microscopy analysis
(FESEM, TEM, XPS) showed effective purification of MWCNTs
under acid treatment, and better dispersion under both chemical and
physical functionalization techniques combined, in their respective
order. Tensile tests showed increase in tensile strength for the
nanocomposites that contain MWCNTs up to 2 wt%. A decrease in
tensile strength was seen in samples that contain 4 wt% of MWCNTs
for both raw and Triton X-100 functionalized, signifying MWCNT
degradation/rebundling at composition with higher content of
MWCNTs. For the acid-treated MWCNTs, however, the tensile
results showed slight improvement even at 4wt%, indicating effective
dispersion of MWCNTs.
Abstract: This paper presents an efficient emission constrained
economic dispatch algorithm that deals with nonlinear cost function
and constraints. It is then incorporated into the dynamic
programming based hydrothermal coordination program. The
program has been tested on a practical utility system having 32
thermal and 12 hydro generating units. Test results show that a slight
increase in production cost causes a substantial reduction in
emission.
Abstract: We have developed a distributed asynchronous Web
based training system. In order to improve the scalability and robustness
of this system, all contents and functions are realized on mobile
agents. These agents are distributed to computers, and they can use
a Peer to Peer network that modified Content-Addressable Network.
In the proposed system, only text data can be included in a exercise.
To make our proposed system more useful, the mechanism that it not
only adapts to multimedia data but also it doesn-t influence the user-s
learning even if the size of exercise becomes large is necessary.
Abstract: In this paper developed and realized absolutely new
algorithm for solving three-dimensional Poisson equation. This
equation used in research of turbulent mixing, computational fluid
dynamics, atmospheric front, and ocean flows and so on. Moreover in
the view of rising productivity of difficult calculation there was
applied the most up-to-date and the most effective parallel
programming technology - MPI in combination with OpenMP
direction, that allows to realize problems with very large data
content. Resulted products can be used in solving of important
applications and fundamental problems in mathematics and physics.
Abstract: The increasing interest in plant sterol enriched foods
is due to the fact that they reduce blood cholesterol concentrations
without adverse side effects. In this context, enriched foods with
phytosterols may be helpful in protecting population against
atherosclerosis and cardiovascular diseases. The aim of the present
work was to evaluate in a population of Viseu, Portugal, the
consumption habits low-fat, plant sterol-enriched yoghurt. For this
study, 577 inquiries were made and the sample was randomly
selected for people shopping in various supermarkets. The
preliminary results showed that the biggest consumers of these
products were women aged 45 to 65 years old. Most of the people
who claimed to buy these products consumed them once a day. Also,
most of the consumers under antidyslipidemic therapeutics noticed
positive effects on hypercholesterolemia.
Abstract: For fire safety purposes, the fire resistance and the
structural behavior of reinforced concrete members are assessed to
satisfy specific fire performance criteria. The available prescribed
provisions are based on standard fire load. Under various fire
scenarios, engineers are in need of both heat transfer analysis and
structural analysis. For heat transfer analysis, the study proposed a
modified finite difference method to evaluate the temperature profile
within a cross section. The research conducted is limited to concrete
sections exposed to a fire on their one side. The method is based on
the energy conservation principle and a pre-determined power
function of the temperature profile. The power value of 2.7 is found
to be a suitable value for concrete sections. The temperature profiles
of the proposed method are only slightly deviate from those of the
experiment, the FEM and the FDM for various fire loads such as
ASTM E 119, ASTM 1529, BS EN 1991-1-2 and 550 oC. The
proposed method is useful to avoid incontinence of the large matrix
system of the typical finite difference method to solve the
temperature profile. Furthermore, design engineers can simply apply
the proposed method in regular spreadsheet software.
Abstract: In the past decade, artificial neural networks (ANNs)
have been regarded as an instrument for problem-solving and
decision-making; indeed, they have already done with a substantial
efficiency and effectiveness improvement in industries and businesses.
In this paper, the Back-Propagation neural Networks (BPNs) will be
modulated to demonstrate the performance of the collaborative
forecasting (CF) function of a Collaborative Planning, Forecasting and
Replenishment (CPFR®) system. CPFR functions the balance between
the sufficient product supply and the necessary customer demand in a
Supply and Demand Chain (SDC). Several classical standard BPN will
be grouped, collaborated and exploited for the easy implementation of
the proposed modular ANN framework based on the topology of a
SDC. Each individual BPN is applied as a modular tool to perform the
task of forecasting SKUs (Stock-Keeping Units) levels that are
managed and supervised at a POS (point of sale), a wholesaler, and a
manufacturer in an SDC. The proposed modular BPN-based CF
system will be exemplified and experimentally verified using lots of
datasets of the simulated SDC. The experimental results showed that a
complex CF problem can be divided into a group of simpler
sub-problems based on the single independent trading partners
distributed over SDC, and its SKU forecasting accuracy was satisfied
when the system forecasted values compared to the original simulated
SDC data. The primary task of implementing an autonomous CF
involves the study of supervised ANN learning methodology which
aims at making “knowledgeable" decision for the best SKU sales plan
and stocks management.