Abstract: Agropyron cristatum L. Gaertn. is a native grass of
semiarid region in Iran which is quit resistant to cool and drought
climate and withstand heavy grazing. This species has close
phylogenetic relationship with Triticum and Hordeum. In this
research, the effect of seven different concentrations of growth
regulator 2,4-D on callus production and somatic embryogenesis of
A. cristatum was investigated on Murashige and Skoog medium. The
results showed that the rate of callus, embryo and neomorph were
highest in 1 mg L-1 2,4-D. Callus production was increased in 1 mg
L-1 2,4-D but dramatically decreased at 5.5 and 9 mg L-1 2,4-D. The
somatic embryos were observed at 1 and 4 mg L-1 2,4-D but matured
embryos and plantlet were only occurred at 1 mg L-1 2,4-D. There
were significant differences between 1 mg L-1 2,4-D and other
treatments for producing globular and torpedo embryos, plantlet,
rooted callus and number of roots (p
Abstract: This study employs the use of the fourth order
Numerov scheme to determine the eigenstates and eigenvalues of
particles, electrons in particular, in single and double delta function
potentials. For the single delta potential, it is found that the
eigenstates could only be attained by using specific potential depths.
The depth of the delta potential well has a value that varies depending
on the delta strength. These depths are used for each well on the
double delta function potential and the eigenvalues are determined.
There are two bound states found in the computation, one with a
symmetric eigenstate and another one which is antisymmetric.
Abstract: Bay leaves have been shown to improve insulin
function in vitro but the effects on people have not been determined.
The objective of this study was to determine if bay leaves may be
important in the prevention and/or alleviation of type 1 diabetes.
Methods: Fifty five people with type 1 diabetes were divided into
two groups, 45 given capsules containing 3 g of bay leaves per day
for 30 days and 10 given a placebo capsules. Results All the patients
consumed bay leaves shows reduced serum glucose with significant
decreases 27% after 30 d. Total cholesterol decreased, 21 %, after 30
days with larger decreases in low density lipoprotein (LDL) 24%.
High density lipoprotein (HDL) increased 20% and Triglycerides
also decreased 26%. There were no significant changes in the
placebo group. Conclusion, this study demonstrates that consumption
of bay leaves, 3 g/d for 30 days, decreases risk factors for diabetes
and cardiovascular diseases and suggests that bay leaves may be
beneficial for people with type 1 diabetes.
Abstract: This study develops a relation to explore the factors influencing management and technology capabilities in strategic alliances. Alliances between firms are recognizing increasingly popular as a vehicle to create and extract greater value from the market. Firm’s alliance can be described as the collaborative problem solving process to solve problems jointly. This study starts from research questions what factors of firm’s management and technology characteristics affect performance of firms which are formed alliances. In this study, we investigated the effect of strategic alliances on company performance. That is, we try to identify whether firms made an alliance with other organizations are differed by characteristics of management and technology. And we test that alliance type and alliance experiences moderate the relationship between firm’s capabilities and its performance. We employ problem-solving perspective and resource-based view perspective to shed light on this research questions. The empirical work is based on the Survey of Business Activities conducted from2006 to 2008 by Statistics Korea. We verify correlations between to point out that these results contribute new empirical evidence on the effect of strategic alliances on company performance.
Abstract: The aim of the current work is to present a comparison among three popular optimization methods in the inverse elastostatics problem (IESP) of flaw detection within a solid. In more details, the performance of a simulated annealing, a Hooke & Jeeves and a sequential quadratic programming algorithm was studied in the test case of one circular flaw in a plate solved by both the boundary element (BEM) and the finite element method (FEM). The proposed optimization methods use a cost function that utilizes the displacements of the static response. The methods were ranked according to the required number of iterations to converge and to their ability to locate the global optimum. Hence, a clear impression regarding the performance of the aforementioned algorithms in flaw identification problems was obtained. Furthermore, the coupling of BEM or FEM with these optimization methods was investigated in order to track differences in their performance.
Abstract: In this paper we propose a novel Run Time Interface
(RTI) technique to provide an efficient environment for MPI jobs on
the heterogeneous architecture of PARAM Padma. It suggests an
innovative, unified framework for the job management interface
system in parallel and distributed computing. This approach employs
proxy scheme. The implementation shows that the proposed RTI is
highly scalable and stable. Moreover RTI provides the storage access
for the MPI jobs in various operating system platforms and improve
the data access performance through high performance C-DAC
Parallel File System (C-PFS). The performance of the RTI is
evaluated by using the standard HPC benchmark suites and the
simulation results show that the proposed RTI gives good
performance on large scale supercomputing system.
Abstract: Bumpers play an important role in preventing the
impact energy from being transferred to the automobile and
passengers. Saving the impact energy in the bumper to be released in
the environment reduces the damages of the automobile and
passengers.
The goal of this paper is to design a bumper with minimum weight
by employing the Glass Material Thermoplastic (GMT) materials.
This bumper either absorbs the impact energy with its deformation or
transfers it perpendicular to the impact direction.
To reach this aim, a mechanism is designed to convert about 80%
of the kinetic impact energy to the spring potential energy and
release it to the environment in the low impact velocity according to
American standard1. In addition, since the residual kinetic energy
will be damped with the infinitesimal elastic deformation of the
bumper elements, the passengers will not sense any impact. It should
be noted that in this paper, modeling, solving and result-s analysis
are done in CATIA, LS-DYNA and ANSYS V8.0 software
respectively.
Abstract: The log periodogram regression is widely used in empirical
applications because of its simplicity, since only a least squares
regression is required to estimate the memory parameter, d, its good
asymptotic properties and its robustness to misspecification of the
short term behavior of the series. However, the asymptotic distribution
is a poor approximation of the (unknown) finite sample distribution
if the sample size is small. Here the finite sample performance of different
nonparametric residual bootstrap procedures is analyzed when
applied to construct confidence intervals. In particular, in addition to
the basic residual bootstrap, the local and block bootstrap that might
adequately replicate the structure that may arise in the errors of the
regression are considered when the series shows weak dependence in
addition to the long memory component. Bias correcting bootstrap
to adjust the bias caused by that structure is also considered. Finally,
the performance of the bootstrap in log periodogram regression based
confidence intervals is assessed in different type of models and how
its performance changes as sample size increases.
Abstract: Purpose of this work is the development of an
automatic classification system which could be useful for radiologists
in the investigation of breast cancer. The software has been designed
in the framework of the MAGIC-5 collaboration.
In the automatic classification system the suspicious regions with
high probability to include a lesion are extracted from the image as
regions of interest (ROIs). Each ROI is characterized by some
features based on morphological lesion differences.
Some classifiers as a Feed Forward Neural Network, a K-Nearest
Neighbours and a Support Vector Machine are used to distinguish the
pathological records from the healthy ones.
The results obtained in terms of sensitivity (percentage of
pathological ROIs correctly classified) and specificity (percentage of
non-pathological ROIs correctly classified) will be presented through
the Receive Operating Characteristic curve (ROC). In particular the
best performances are 88% ± 1 of area under ROC curve obtained
with the Feed Forward Neural Network.
Abstract: We have proposed an information filtering system
using index word selection from a document set based on the
topics included in a set of documents. This method narrows
down the particularly characteristic words in a document set
and the topics are obtained by Sparse Non-negative Matrix
Factorization. In information filtering, a document is often
represented with the vector in which the elements correspond
to the weight of the index words, and the dimension of the
vector becomes larger as the number of documents is
increased. Therefore, it is possible that useless words as index
words for the information filtering are included. In order to
address the problem, the dimension needs to be reduced. Our
proposal reduces the dimension by selecting index words
based on the topics included in a document set. We have
applied the Sparse Non-negative Matrix Factorization to the
document set to obtain these topics. The filtering is carried out
based on a centroid of the learning document set. The centroid
is regarded as the user-s interest. In addition, the centroid is
represented with a document vector whose elements consist of
the weight of the selected index words. Using the English test
collection MEDLINE, thus, we confirm the effectiveness of
our proposal. Hence, our proposed selection can confirm the
improvement of the recommendation accuracy from the other
previous methods when selecting the appropriate number of
index words. In addition, we discussed the selected index
words by our proposal and we found our proposal was able to
select the index words covered some minor topics included in
the document set.
Abstract: Text similarity measurement is a fundamental issue in
many textual applications such as document clustering, classification,
summarization and question answering. However, prevailing approaches
based on Vector Space Model (VSM) more or less suffer
from the limitation of Bag of Words (BOW), which ignores the semantic
relationship among words. Enriching document representation
with background knowledge from Wikipedia is proven to be an effective
way to solve this problem, but most existing methods still
cannot avoid similar flaws of BOW in a new vector space. In this
paper, we propose a novel text similarity measurement which goes
beyond VSM and can find semantic affinity between documents.
Specifically, it is a unified graph model that exploits Wikipedia as
background knowledge and synthesizes both document representation
and similarity computation. The experimental results on two different
datasets show that our approach significantly improves VSM-based
methods in both text clustering and classification.
Abstract: A solar powered air heating system using one ended evacuated tubes is experimentally investigated. A solar air heater containing forty evacuated tubes is used for heating purpose. The collector surface area is about 4.44 m2. The length and outer diameters of the outer glass tube and absorber tube are 1500, 47 and 37 mm, respectively. In this experimental setup, we have a header (heat exchanger) of square shape (190 mm x 190 mm). The length of header is 1500 mm. The header consists of a hollow pipe in the center whose diameter is 60 mm through which the air is made to flow. The experimental setup contains approximately 108 liters of water. Water is working as heat collecting medium which collects the solar heat falling on the tubes. This heat is delivered to the air flowing through the header pipe. This heat flow is due to natural convection and conduction. The outlet air temperature depends upon several factors along with air flow rate and solar radiation intensity. The study has been done for both up-flow and down-flow of air in header in similar weather conditions, at different flow rates. In the present investigations the study has been made to find the effect of intensity of solar radiations and flow rate of air on the out let temperature of the air with time and which flow is more efficient. The obtained results show that the system is highly effective for the heating in this region. Moreover, it has been observed that system is highly efficient for the particular flow rate of air. It was also observed that downflow configuration is more effective than up-flow condition at all flow rates due to lesser losses in down-flow. The results show that temperature differences of upper head and lower head, both of water and surface of pipes on the respective ends is lower in down-flow.
Abstract: The morphological short-term evolution of Ponta do Tubarão Island (PTI) was investigated through high accurate surveys based on post-processed kinematic (PPK) relative positioning on Global Navigation Satellite Systems (GNSS). PTI is part of a barrier island system on a high energy northeast Brazilian coastal environment and also an area of high environmental sensitivity. Surveys were carried out quarterly over a two years period from May 2010 to May 2012. This paper assesses statically the performance of digital elevation models (DEM) derived from different interpolation methods to represent morphologic features and to quantify volumetric changes and TIN models shown the best results to that purposes. The MDE allowed quantifying surfaces and volumes in detail as well as identifying the most vulnerable segments of the PTI to erosion and/or accumulation of sediments and relate the alterations to climate conditions. The coastal setting and geometry of PTI protects a significant mangrove ecosystem and some oil and gas facilities installed in the vicinities from damaging effects of strong oceanwaves and currents. Thus, the maintenance of PTI is extremely required but the prediction of its longevity is uncertain because results indicate an irregularity of sedimentary balance and a substantial decline in sediment supply to this coastal area.
Abstract: Cryo-electron microscopy (CEM) in combination with
single particle analysis (SPA) is a widely used technique for
elucidating structural details of macromolecular assemblies at closeto-
atomic resolutions. However, development of automated software
for SPA processing is still vital since thousands to millions of
individual particle images need to be processed. Here, we present our
workflow for automated particle picking. Our approach integrates
peak shape analysis to the classical correlation and an iterative
approach to separate macromolecules and background by
classification. This particle selection workflow furthermore provides
a robust means for SPA with little user interaction. Processing
simulated and experimental data assesses performance of the
presented tools.
Abstract: Spam mails are unwanted mails sent to large number
of users. Spam mails not only consume the network resources, but
cause security threats as well. This paper proposes an efficient
technique to detect, and to prevent spam mail in the sender side rather
than the receiver side. This technique is based on a counter set on the
sender server. When a mail is transmitted to the server, the mail server
checks the number of the recipients based on its counter policy. The
counter policy performed by the mail server is based on some
pre-defined criteria. When the number of recipients exceeds the
counter policy, the mail server discontinues the rest of the process, and
sends a failure mail to sender of the mail; otherwise the mail is
transmitted through the network. By using this technique, the usage of
network resources such as bandwidth, and memory is preserved. The
simulation results in real network show that when the counter is set on
the sender side, the time required for spam mail detection is 100 times
faster than the time the counter is set on the receiver side, and the
network resources are preserved largely compared with other
anti-spam mail techniques in the receiver side.
Abstract: Genome profiling (GP), a genotype based technology, which exploits random PCR and temperature gradient gel electrophoresis, has been successful in identification/classification of organisms. In this technology, spiddos (Species identification dots) and PaSS (Pattern similarity score) were employed for measuring the closeness (or distance) between genomes. Based on the closeness (PaSS), we can buildup phylogenetic trees of the organisms. We noticed that the topology of the tree is rather robust against the experimental fluctuation conveyed by spiddos. This fact was confirmed quantitatively in this study by computer-simulation, providing the limit of the reliability of this highly powerful methodology. As a result, we could demonstrate the effectiveness of the GP approach for identification/classification of organisms.
Abstract: Nonlinear and unbalance loads in three phase
networks create harmonics and losses. Active and passive filters are
used for elimination or reduction of these effects. Passive filters have
some limitations. For example, they are designed only for a specific
frequency and they may cause to resonance in the network at the
point of common coupling. The other drawback of a passive filter is
that the sizes of required elements are normally large. The active
filter can improve some of limitations of passive filter for example;
they can eliminate more than one harmonic and don't cause resonance
in the network. In this paper inverter analysis have been done
simultaneously in three phase and the RL impedance of the line have
been considered. A sliding mode control based on energy feedback of
capacitors is employed in the design with this method, the dynamic
speed of the filter is improved effectively and harmonics and load
unbalance is compensating quickly.
Abstract: Clustering categorical data is more complicated than
the numerical clustering because of its special properties. Scalability
and memory constraint is the challenging problem in clustering large
data set. This paper presents an incremental algorithm to cluster the
categorical data. Frequencies of attribute values contribute much in
clustering similar categorical objects. In this paper we propose new
similarity measures based on the frequencies of attribute values and
its cardinalities. The proposed measures and the algorithm are
experimented with the data sets from UCI data repository. Results
prove that the proposed method generates better clusters than the
existing one.
Abstract: Recently, permeable breakwaters have been suggested to overcome the disadvantages of fully protection breakwaters. These protection structures have minor impacts on the coastal environment and neighboring beaches where they provide a more economical protection from waves and currents. For regular waves, a numerical model is used (FLOW-3D, VOF) to investigate the hydraulic performance of a permeable breakwater. The model of permeable breakwater consists of a pair of identical vertical slotted walls with an impermeable upper and lower part, where the draft is a decimal multiple of the total depth. The middle part is permeable with a porosity of 50%. The second barrier is located at distant of 0.5 and 1.5 of the water depth from the first one. The numerical model is validated by comparisons with previous laboratory data and semi-analytical results of the same model. A good agreement between the numerical results and both laboratory data and semi-analytical results has been shown and the results indicate the applicability of the numerical model to reproduce most of the important features of the interaction. Through the numerical investigation, the friction factor of the model is carefully discussed.
Abstract: An important structuring mechanism for knowledge bases is building clusters based on the content of their knowledge objects. The objects are clustered based on the principle of maximizing the intraclass similarity and minimizing the interclass similarity. Clustering can also facilitate taxonomy formation, that is, the organization of observations into a hierarchy of classes that group similar events together. Hierarchical representation allows us to easily manage the complexity of knowledge, to view the knowledge at different levels of details, and to focus our attention on the interesting aspects only. One of such efficient and easy to understand systems is Hierarchical Production rule (HPRs) system. A HPR, a standard production rule augmented with generality and specificity information, is of the following form Decision If < condition> Generality Specificity . HPRs systems are capable of handling taxonomical structures inherent in the knowledge about the real world. In this paper, a set of related HPRs is called a cluster and is represented by a HPR-tree. This paper discusses an algorithm based on cumulative learning scenario for dynamic structuring of clusters. The proposed scheme incrementally incorporates new knowledge into the set of clusters from the previous episodes and also maintains summary of clusters as Synopsis to be used in the future episodes. Examples are given to demonstrate the behaviour of the proposed scheme. The suggested incremental structuring of clusters would be useful in mining data streams.