Abstract: The major building block of most elliptic curve cryptosystems
are computation of multi-scalar multiplication. This paper
proposes a novel algorithm for simultaneous multi-scalar multiplication,
that is by employing addition chains. The previously known
methods utilizes double-and-add algorithm with binary representations.
In order to accomplish our purpose, an efficient empirical
method for finding addition chains for multi-exponents has been
proposed.
Abstract: MicroRNAs (miRNAs) are small, non-coding and
regulatory RNAs about 20 to 24 nucleotides long. Their conserved
nature among the various organisms makes them a good source of
new miRNAs discovery by comparative genomics approach. The
study resulted in 21 miRNAs of 20 pre-miRNAs belonging to 16
families (miR156, 157, 158, 164, 165, 168, 169, 172, 319, 390, 393,
394, 395, 400, 472 and 861) in evergreen spruce tree (Picea). The
miRNA families; miR 157, 158, 164, 165, 168, 169, 319, 390, 393,
394, 400, 472 and 861 are reported for the first time in the Picea. All
20 miRNA precursors form stable minimum free energy stem-loop
structure as their orthologues form in Arabidopsis and the mature
miRNA reside in the stem portion of the stem loop structure. Sixteen
(16) miRNAs are from Picea glauca and five (5) belong to Picea
sitchensis. Their targets consist of transcription factors, growth
related, stressed related and hypothetical proteins.
Abstract: State-dependent Riccati equation based controllers are
becoming increasingly popular because of having attractive
properties like optimality, stability and robustness. This paper focuses
on the design of a roll autopilot for a fin stabilized and canard
controlled 122mm artillery rocket using state-dependent Riccati
equation technique. Initial spin is imparted to rocket during launch
and it quickly decays due to straight tail fins. After the spin phase, the
roll orientation of rocket is brought to zero with the canard deflection
commands generated by the roll autopilot. Roll autopilot has been
developed by considering uncoupled roll, pitch and yaw channels.
The canard actuator is modeled as a second-order nonlinear system.
Elements of the state weighing matrix for Riccati equation have been
chosen to be state dependent to exploit the design flexibility offered
by the Riccati equation technique. Simulation results under varying
conditions of flight demonstrate the wide operating range of the
proposed autopilot.
Abstract: We have developed a database for membrane protein functions, which has more than 3000 experimental data on functionally important amino acid residues in membrane proteins along with sequence, structure and literature information. Further, we have proposed different methods for identifying membrane proteins based on their functions: (i) discrimination of membrane transport proteins from other globular and membrane proteins and classifying them into channels/pores, electrochemical and active transporters, and (ii) β-signal for the insertion of mitochondrial β-barrel outer membrane proteins and potential targets. Our method showed an accuracy of 82% in discriminating transport proteins and 68% to classify them into three different transporters. In addition, we have identified a motif for targeting β-signal and potential candidates for mitochondrial β-barrel membrane proteins. Our methods can be used as effective tools for genome-wide annotations.
Abstract: In the area where the high quality water is not
available, unconventional water sources are used to irrigate.
Household leachate is one of the sources which are used in dry and
semi dry areas in order to water the barer trees and plants. It meets
the plants needs and also has some effects on the soil, but at the same
time it might cause some problems as well. This study in order to
evaluate the effect of using Compost leachate on the density of soil
iron in form of a statistical pattern called ''Split Plot'' by using two
main treatments, one subsidiary treatment and three repetitions of the
pattern in a three month period. The main N treatments include:
irrigation using well water as a blank treatments and the main I
treatments include: irrigation using leachate and well water
concurrently. Some subsidiary treatments were DI (Drop Irrigation)
and SDI (Sub Drop Irrigation). Then in the established plots, 36
biannual pine and cypress shrubs were randomly grown. Two months
later the treatment begins. The results revealed that there was a
significant variation between the main treatment and the instance
regarding pH decline in the soil which was related to the amount of
leachate injected into the soil. After some time and using leachate the
pH level fell, as much as 0.46 and also increased due to the great
amounts of leachate. The underneath drop irrigation ends in better
results than sub drop irrigation since it keeps the soil texture fixed.
Abstract: As part of national epidemiological survey on bovine
viral diarrhea virus (BVDV), a total of 274 dejecta samples were
collected from 14 cattle farms in 8 areas of Xinjiang Uygur
Autonomous Region in northwestern China. Total RNA was extracted
from each sample, and 5--untranslated region (UTR) of BVDV
genome was amplified by using two-step reverse
transcriptase-polymerase chain reaction (RT-PCR). The PCR products
were subsequently sequenced to study the genetic variations of BVDV
in these areas. Among the 274 samples, 33 samples were found
virus-positive. According to sequence analysis of the PCR products,
the 33 samples could be arranged into 16 groups. All the sequences,
however, were highly conserved with BVDV Osloss strains. The virus
possessed theses sequences belonged to BVDV-1b subtype by
phylogenetic analysis. Based on these data, we established a typing
tree for BVDV in these areas. Our results suggested that BVDV-1b
was a predominant subgenotype in northwestern China and no
correlation between the genetic and geographical distances could be
observed above the farm level.
Abstract: Non-viral gene carriers composed of biodegradable
polymers or lipids have been considered as a safer alternative for gene
carriers over viral vectors. We have developed multi-functional
nano-micelles for both drug and gene delivery application.
Polyethyleneimine (PEI) was modified by grafting stearic acid (SA)
and formulated to polymeric micelles (PEI-SA) with positive surface
charge for gene and drug delivery. Our results showed that PEI-SA
micelles provided high siRNA binding efficiency. In addition, siRNA
delivered by PEI-SA carriers also demonstrated significantly high
cellular uptake even in the presence of serum proteins. The
post-transcriptional gene silencing efficiency was greatly improved by
the polyplex formulated by 10k PEI-SA/siRNA. The amphiphilic
structure of PEI-SA micelles provided advantages for multifunctional
tasks; where the hydrophilic shell modified with cationic charges can
electrostatically interact with DNA or siRNA, and the hydrophobic
core can serve as payloads for hydrophobic drugs, making it a
promising multifunctional vehicle for both genetic and chemotherapy
application.
Abstract: Nowadays, where most of the leading economies are
service oriented and e-business is being widely used for their
management, supply chain management has become one of the most
studied and practiced fields. Quality has an important role on today-s
business processes, so it is important to understand the impact of IT
service quality on the performance of supply chains. This paper will
start by analyzing the Supply Chain Operations Reference (SCOR)
model and each of its five activities: Plan, Source, Make, Delivery,
and Return. This article proposes a framework for analyzing Effect of
IT Service Quality on Supply Chain Performance. Using the
proposed framework, hypotheses are framed for the direct effect of IT
service quality on Supply Chain Performance and its indirect effect
through effective Supply Chain Management. The framework will be
validated empirically based on the surveys of executives of various
organizations and statistical analyses of the data collected.
Abstract: It is important problems to increase the detection rates
and reduce false positive rates in Intrusion Detection System (IDS).
Although preventative techniques such as access control and
authentication attempt to prevent intruders, these can fail, and as a
second line of defence, intrusion detection has been introduced. Rare
events are events that occur very infrequently, detection of rare
events is a common problem in many domains. In this paper we
propose an intrusion detection method that combines Rough set and
Fuzzy Clustering. Rough set has to decrease the amount of data and
get rid of redundancy. Fuzzy c-means clustering allow objects to
belong to several clusters simultaneously, with different degrees of
membership. Our approach allows us to recognize not only known
attacks but also to detect suspicious activity that may be the result of
a new, unknown attack. The experimental results on Knowledge
Discovery and Data Mining-(KDDCup 1999) Dataset show that the
method is efficient and practical for intrusion detection systems.
Abstract: The present work represents an investigation of the
hydrolysis of hull-less pumpkin (Cucurbita Pepo L.) oil cake protein
isolate (PuOC PI) by pepsin. To examine the effectiveness and
suitability of pepsin towards PuOC PI the kinetic parameters for
pepsin on PuOC PI were determined and then, the hydrolysis process
was studied using Response Surface Methodology (RSM). The
hydrolysis was carried out at temperature of 30°C and pH 3.00. Time
and initial enzyme/substrate ratio (E/S) at three levels were selected
as the independent parameters. The degree of hydrolysis, DH, was
mesuared after 20, 30 and 40 minutes, at initial E/S of 0.7, 1 and 1.3
mA/mg proteins. Since the proposed second-order polynomial model
showed good fit with the experimental data (R2 = 0.9822), the
obtained mathematical model could be used for monitoring the
hydrolysis of PuOC PI by pepsin, under studied experimental
conditions, varying the time and initial E/S. To achieve the highest
value of DH (39.13 %), the obtained optimum conditions for time
and initial E/S were 30 min and 1.024 mA/mg proteins.
Abstract: The process of laser absorption in the skin during
laser irradiation was a critical point in medical application
treatments. Delivery the correct amount of laser light is a critical
element in photodynamic therapy (PDT). More amounts of laser
light able to affect tissues in the skin and small amount not able to
enhance PDT procedure in skin. The knowledge of the skin tone
laser dependent distribution of 635 nm radiation and its penetration
depth in skin is a very important precondition for the investigation of
advantage laser induced effect in (PDT) in epidermis diseases
(psoriasis). The aim of this work was to estimate an optimum effect
of diode laser (635 nm) on the treatment of epidermis diseases in
different color skin. Furthermore, it is to improve safety of laser in
PDT in epidermis diseases treatment. Advanced system analytical
program (ASAP) which is a new approach in investigating the PDT,
dependent on optical properties of different skin color was used in
present work. A two layered Realistic Skin Model (RSM); stratum
corneum and epidermal with red laser (635 nm, 10 mW) were used
for irradiative transfer to study fluence and absorbance in different
penetration for various human skin colors. Several skin tones very
fair, fair, light, medium and dark are used to irradiative transfer. This
investigation involved the principles of laser tissue interaction when
the skin optically injected by a red laser diode. The results
demonstrated that the power characteristic of a laser diode (635 nm)
can affect the treatment of epidermal disease in various color skins.
Power absorption of the various human skins were recorded and
analyzed in order to find the influence of the melanin in PDT
treatment in epidermal disease. A two layered RSM show that the
change in penetration depth in epidermal layer of the color skin has a
larger effect on the distribution of absorbed laser in the skin; this is
due to the variation of the melanin concentration for each color.
Abstract: Diatoms are an important group of aquatic ecosystems and diatom-based indices are increasingly becoming important tools for the assessment of ecological conditions in lotic systems. Although the studies are very limited about Turkish rivers, diatom indices were used for monitoring rivers in different basins. In the present study, we used OMNIDIA program for estimation of stream quality. Some indices have less sensitive (IDP, WAT, LOBO, GENRE, TID, CEE, PT), intermediate sensitivities (IDSE, DESCY, IPS, DI-CH, SLA, IDAP), the others higher sensitivities (SID, IBD, SHE, EPI-D). Among the investigated diatom communities, only a few taxa indicated alfa-mesosaprobity and polysaprobity. Most of the sites were characterized by a great relative contribution of eutraphent and tolerant ones as well as oligosaprobic and betamesosaprobic diatoms. In general, SID and IBD indices gave the best results. This study suggests that the structure of benthic diatom communities and diatom indices, especially SID, can be applied for monitoring rivers in Southern Turkey.
Abstract: Emerging Bio-engineering fields such as Brain
Computer Interfaces, neuroprothesis devices and modeling and
simulation of neural networks have led to increased research activity
in algorithms for the detection, isolation and classification of Action
Potentials (AP) from noisy data trains. Current techniques in the field
of 'unsupervised no-prior knowledge' biosignal processing include
energy operators, wavelet detection and adaptive thresholding. These
tend to bias towards larger AP waveforms, AP may be missed due to
deviations in spike shape and frequency and correlated noise
spectrums can cause false detection. Also, such algorithms tend to
suffer from large computational expense.
A new signal detection technique based upon the ideas of phasespace
diagrams and trajectories is proposed based upon the use of a
delayed copy of the AP to highlight discontinuities relative to
background noise. This idea has been used to create algorithms that
are computationally inexpensive and address the above problems.
Distinct AP have been picked out and manually classified from
real physiological data recorded from a cockroach. To facilitate
testing of the new technique, an Auto Regressive Moving Average
(ARMA) noise model has been constructed bases upon background
noise of the recordings. Along with the AP classification means this
model enables generation of realistic neuronal data sets at arbitrary
signal to noise ratio (SNR).
Abstract: The present energy situation and the concerns
about global warming has stimulated active research interest
in non-petroleum, carbon free compounds and non-polluting
fuels, particularly for transportation, power generation, and
agricultural sectors. Environmental concerns and limited
amount of petroleum fuels have caused interests in the
development of alternative fuels for internal combustion (IC)
engines. The petroleum crude reserves however, are declining
and consumption of transport fuels particularly in the
developing countries is increasing at high rates. Severe
shortage of liquid fuels derived from petroleum may be faced
in the second half of this century. Recently more and more
stringent environmental regulations being enacted in the USA
and Europe have led to the research and development
activities on clean alternative fuels. Among the gaseous fuels
hydrogen is considered to be one of the clean alternative fuel.
Hydrogen is an interesting candidate for future internal
combustion engine based power trains. In this experimental
investigation, the performance and combustion analysis were
carried out on a direct injection (DI) diesel engine using
hydrogen with diesel following the TMI(Time Manifold
Injection) technique at different injection timings of 10
degree,45 degree and 80 degree ATDC using an electronic
control unit (ECU) and injection durations were controlled.
Further, the tests have been carried out at a constant speed of
1500rpm at different load conditions and it can be observed
that brake thermal efficiency increases with increase in load
conditions with a maximum gain of 15% at full load
conditions during all injection strategies of hydrogen. It was
also observed that with the increase in hydrogen energy share
BSEC started reducing and it reduced to a maximum of 9% as
compared to baseline diesel at 10deg ATDC injection during
maximum injection proving the exceptional combustion
properties of hydrogen.
Abstract: In this research, the laminar heat transfer of natural convection on vertical surfaces has been investigated. Most of the studies on natural convection have been considered constantly whereas velocity and temperature domain, do not change with time, transient one are used a lot. Governing equations are solved using a finite volume approach. The convective terms are discretized using the power-law scheme, whereas for diffusive terms the central difference is employed. Coupling between the velocity and pressure is made with SIMPLE algorithm. The resultant system of discretized linear algebraic equations is solved with an alternating direction implicit scheme. Then a configuration of rectangular fins is put in different ways on the surface and heat transfer of natural convection on these surfaces without sliding is studied and finally optimization is done.
Abstract: As one result of the project “Reactive Construction
Project Scheduling using Real Time Construction Logistic Data and
Simulation”, a procedure for using data about uncertain resource
availability assumptions in reactive scheduling processes has been
developed. Prediction data about resource availability is generated in
a formalized way using real-time monitoring data e.g. from auto-ID
systems on the construction site and in the supply chains. The paper
focusses on the formalization of the procedure for monitoring
construction logistic processes, for the detection of disturbance and
for generating of new and uncertain scheduling assumptions for the
reactive resource constrained simulation procedure that is and will be
further described in other papers.
Abstract: Support vector machines (SVMs) have shown
superior performance compared to other machine learning techniques,
especially in classification problems. Yet one limitation of SVMs is
the lack of an explanation capability which is crucial in some
applications, e.g. in the medical and security domains. In this paper, a
novel approach for eclectic rule-extraction from support vector
machines is presented. This approach utilizes the knowledge acquired
by the SVM and represented in its support vectors as well as the
parameters associated with them. The approach includes three stages;
training, propositional rule-extraction and rule quality evaluation.
Results from four different experiments have demonstrated the value
of the approach for extracting comprehensible rules of high accuracy
and fidelity.
Abstract: Modernizing legacy applications is the key issue facing IT managers today because there's enormous pressure on organizations to change the way they run their business to meet the new requirements. The importance of software maintenance and reengineering is forever increasing. Understanding the architecture of existing legacy applications is the most critical issue for maintenance and reengineering. The artifacts recovery can be facilitated with different recovery approaches, methods and tools. The existing methods provide static and dynamic set of techniques for extracting architectural information, but are not suitable for all users in different domains. This paper presents a simple and lightweight pattern extraction technique to extract different artifacts from legacy systems using regular expression pattern specifications with multiple language support. We used our custom-built tool DRT to recover artifacts from existing system at different levels of abstractions. In order to evaluate our approach a case study is conducted.
Abstract: Nowadays predicting political risk level of country
has become a critical issue for investors who intend to achieve
accurate information concerning stability of the business
environments. Since, most of the times investors are layman and
nonprofessional IT personnel; this paper aims to propose a
framework named GECR in order to help nonexpert persons to
discover political risk stability across time based on the political
news and events.
To achieve this goal, the Bayesian Networks approach was
utilized for 186 political news of Pakistan as sample dataset.
Bayesian Networks as an artificial intelligence approach has been
employed in presented framework, since this is a powerful technique
that can be applied to model uncertain domains. The results showed
that our framework along with Bayesian Networks as decision
support tool, predicted the political risk level with a high degree of
accuracy.
Abstract: Data mining and knowledge engineering have become a tough task due to the availability of large amount of data in the web nowadays. Validity and reliability of data also become a main debate in knowledge acquisition. Besides, acquiring knowledge from different languages has become another concern. There are many language translators and corpora developed but the function of these translators and corpora are usually limited to certain languages and domains. Furthermore, search results from engines with traditional 'keyword' approach are no longer satisfying. More intelligent knowledge engineering agents are needed. To address to these problems, a system known as Multilingual Word Semantic Network is proposed. This system adapted semantic network to organize words according to concepts and relations. The system also uses open source as the development philosophy to enable the native language speakers and experts to contribute their knowledge to the system. The contributed words are then defined and linked using lexical and semantic relations. Thus, related words and derivatives can be identified and linked. From the outcome of the system implementation, it contributes to the development of semantic web and knowledge engineering.