Abstract: Cast metal inlays can be used on molars requiring a
class II restoration instead amalgam and offer a durable alternative.
Because it is known that class II inlays may increase the
susceptibility to fracture, it is important to ensure optimal
performance in selection of the adequate preparation design to reduce
stresses in teeth structures and also in the restorations. The aim of the
study was to investigate the influence of preparation design on stress
distribution in molars with different class II preparations and in cast
metal inlays. The first step of the study was to achieve 3D models in
order to analyze teeth and cast metal class II inlays. The geometry of
the intact tooth was obtained by 3D scanning using a manufactured
device. With a NURBS modeling program the preparations and the
appropriately inlays were designed. 3D models of first upper molars
of the same shape and size were created. Inlay cavities designs were
created using literature data. The geometrical model was exported
and the mesh structure of the solid 3D model was created for
structural simulations. Stresses were located around the occlusal
contact areas. For the studied cases, the stress values were not
significant influenced by the taper of the preparation. it was
demonstrated stresses are higher in the cast metal restorations and
therefore the strength of the teeth is not affected.
Abstract: Plasma plume will be produced and arrive at spacecraft when the electric thruster operates on orbit. It-s important to characterize the thruster plasma parameters because the plume has significant effects or hazards on spacecraft sub-systems and parts. Through the ground test data of the desired parameters, the major characteristics of the thruster plume will be achieved. Also it is very important for optimizing design of Ion thruster. Retarding Potential Analyzer (RPA) is an effective instrument for plasma ion energy per unit charge distribution measurement. Special RPA should be designed according to certain plume plasma parameters range and feature. In this paper, major principles usable for good RPA design are discussed carefully. Conform to these principles, a four-grid planar electrostatic energy analyzer RPA was designed to avoid false data, and details were discussed including construction, materials, aperture diameter and so on. At the same time, it was designed more suitable for credible and long-duration measurements in the laboratory. In the end, RPA measurement results in the laboratory were given and discussed.
Abstract: The two agro-ecological zones became the focus of
the study because of violent nature of the incessant conflict in the
zones. The available register of farmers association was the sampling
frame work where ten percent (61) farmers per state were randomly
sampled. Data were collected and analysed using z-test. The research
findings revealed tree crops and grains production enterprises ranked
higher in Osun (rain fed zones) and Taraba states (savannah zones)
respectively. Osun state entrepreneur felt the effect of the conflict on
their enterprises more than Tarba state. The reasons adduced for
severity of the conflict on enterprises are majority (77.0%) migrated
and (75.5%) of them were not allowed to enter their farms during and
when conflict deescalated unlike situation in Taraba state. The
different in enterprises production level between the two agroecological
zone was statistically significant at p
Abstract: Decision support systems are usually based on
multidimensional structures which use the concept of hypercube.
Dimensions are the axes on which facts are analyzed and form a
space where a fact is located by a set of coordinates at the
intersections of members of dimensions. Conventional
multidimensional structures deal with discrete facts linked to discrete
dimensions. However, when dealing with natural continuous
phenomena the discrete representation is not adequate. There is a
need to integrate spatiotemporal continuity within multidimensional
structures to enable analysis and exploration of continuous field data.
Research issues that lead to the integration of spatiotemporal
continuity in multidimensional structures are numerous. In this paper,
we discuss research issues related to the integration of continuity in
multidimensional structures, present briefly a multidimensional
model for continuous field data. We also define new aggregation
operations. The model and the associated operations and measures
are validated by a prototype.
Abstract: Feature-based registration is an effective technique for clinical use, because it can greatly reduce computational costs. However, this technique, which estimates the transformation by using feature points extracted from two images, may cause misalignments. To handle with this limitation, we propose to extract the salient edges and extracted control points (CP) of medical images by using efficiency of multiresolution representation of data nonsubsampled contourlet transform (NSCT) that finds the best feature points. The MR images were first decomposed using the NSCT, and then Edge and CP were extracted from bandpass directional subband of NSCT coefficients and some proposed rules. After edge and CP extraction, mutual information was adopted for the registration of feature points and translation parameters are calculated by using particle swarm optimization (PSO). The experimental results showed that the proposed method produces totally accurate performance for registration medical CT-MR images.
Abstract: ebXML (Electronic Business using eXtensible
Markup Language) is an e-business standard, sponsored by
UN/CEFACT and OASIS, which enables enterprises to exchange
business messages, conduct trading relationships, communicate
data in common terms and define and register business
processes. While there is tremendous e-business value in the
ebXML, security remains an unsolved problem and one of the
largest barriers to adoption. XML security technologies emerging
recently have extensibility and flexibility suitable for security
implementation such as encryption, digital signature, access
control and authentication.
In this paper, we propose ebXML business transaction models
that allow trading partners to securely exchange XML based
business transactions by employing XML security technologies.
We show how each XML security technology meets the ebXML
standard by constructing the test software and validating messages
between the trading partners.
Abstract: In article the data of acute toxicity for pre-clinical
researches of Ramon preparation is described. Ramon effects to
clinical characteristics of blood, cardio-vascular system, hepatotoxic
and diuretic effects were studied.
Abstract: With the tremendous growth of World Wide Web
(WWW) data, there is an emerging need for effective information
retrieval at the document level. Several query languages such as
XML-QL, XPath, XQL, Quilt and XQuery are proposed in recent
years to provide faster way of querying XML data, but they still lack of
generality and efficiency. Our approach towards evolving a framework
for querying semistructured documents is based on formal query
algebra. Two elements are introduced in the proposed framework:
first, a generic and flexible data model for logical representation of
semistructured data and second, a set of operators for the manipulation
of objects defined in the data model. In additional to accommodating
several peculiarities of semistructured data, our model offers novel
features such as bidirectional paths for navigational querying and
partitions for data transformation that are not available in other
proposals.
Abstract: For best collaboration, Asynchronous tools and particularly the discussion forums are the most used thanks to their flexibility in terms of time. To convey only the messages that belong to a theme of interest of the tutor in order to help him during his tutoring work, use of a tool for classification of these messages is indispensable. For this we have proposed a semantics classification tool of messages of a discussion forum that is based on LSA (Latent Semantic Analysis), which includes a thesaurus to organize the vocabulary. Benefits offered by formal ontology can overcome the insufficiencies that a thesaurus generates during its use and encourage us then to use it in our semantic classifier. In this work we propose the use of some functionalities that a OWL ontology proposes. We then explain how functionalities like “ObjectProperty", "SubClassOf" and “Datatype" property make our classification more intelligent by way of integrating new terms. New terms found are generated based on the first terms introduced by tutor and semantic relations described by OWL formalism.
Abstract: Transportation authorities need to provide the services
and facilities that are critical to every country-s well-being and
development. Management of the road network is becoming
increasingly challenging as demands increase and resources are
limited. Public sector institutions are integrating performance
information into budgeting, managing and reporting via
implementing performance measurement systems. In the face of
growing challenges, performance measurement of road networks is
attracting growing interest in many countries. The large scale of
public investments makes the maintenance and development of road
networks an area where such systems are an important assessment
tool. Transportation agencies have been using performance
measurement and modeling as part of pavement and bridge
management systems. Recently the focus has been on extending the
process to applications in road construction and maintenance
systems, operations and safety programs, and administrative
structures and procedures. To eliminate failure and dysfunctional
consequences the importance of obtaining objective data and
implementing evaluation instrument where necessary is presented in
this paper
Abstract: There are various solutions for improving existing overhead line systems with the general purpose of increasing their limited capacity. The capacity reserve of the existing overhead lines is an important problem that must be considered from different aspects. The paper contains a comparative analysis of the mechanical and thermal limitations of an existing overhead line based on certain calculation conditions characterizing the examined variants. The methodology of the proposed estimation of the permissible conductor temperature and maximum load current is described in detail. The transmission line model consists of specific information of an existing overhead line of the Latvian power network. The main purpose of the simulation tasks is to find an additional capacity reserve by using accurate mathematical models. The results of the obtained data are presented.
Abstract: Studies on gas solid mass transfer using Supercritical fluid CO2 (SC-CO2) in a packed bed of palm kernels was investigated at operating conditions of temperature 50 °C and 70 °C and pressures ranges from 27.6 MPa, 34.5 MPa, 41.4 MPa and 48.3 MPa. The development of mass transfer models requires knowledge of three properties: the diffusion coefficient of the solute, the viscosity and density of the Supercritical fluids (SCF). Matematical model with respect to the dimensionless number of Sherwood (Sh), Schmidt (Sc) and Reynolds (Re) was developed. It was found that the model developed was found to be in good agreement with the experimental data within the system studied.
Abstract: This paper evaluates the performance of a novel
algorithm for tracking of a mobile node, interms of execution time
and root mean square error (RMSE). Particle Filter algorithm is used
to track the mobile node, however a new technique in particle filter
algorithm is also proposed to reduce the execution time. The
stationary points were calculated through trilateration and finally by
averaging the number of points collected for a specific time, whereas
tracking is done through trilateration as well as particle filter
algorithm. Wi-Fi signal is used to get initial guess of the position of
mobile node in x-y coordinates system. Commercially available
software “Wireless Mon" was used to read the WiFi signal strength
from the WiFi card. Visual Cµ version 6 was used to interact with
this software to read only the required data from the log-file
generated by “Wireless Mon" software. Results are evaluated through
mathematical modeling and MATLAB simulation.
Abstract: We have applied new accelerated algorithm for linear
discriminate analysis (LDA) in face recognition with support vector
machine. The new algorithm has the advantage of optimal selection
of the step size. The gradient descent method and new algorithm has
been implemented in software and evaluated on the Yale face
database B. The eigenfaces of these approaches have been used to
training a KNN. Recognition rate with new algorithm is compared
with gradient.
Abstract: The understanding of knee movement during swing
importance for golf swing improving and preventing injury. Thirty
male professional and amateur golfers were assigned to swing time
by time for 3 times. Data from a vedio-based motion capture were
used to compute knee joint movement variables. The results showed
that professional and amateur golfers were significantly in left knee
flexion angle at the impact point and mid follow through phase.
Nevertheless, left knee external rotation in both groups was also
significant. The right knee were no significant different in all
variable. However, pattern of knee joint movement are also likely
between professional and amateur golfers.
Abstract: Shirvan is located in plain in Northern Khorasan province north east of Iran and has semiarid to temperate climate. To investigate the annual changes in some qualitative parameters such as electrical conductivity, total dissolved solids and chloride concentrations which have increased during ten continuous years. Fourteen groundwater sources including deep as well as semi-deep wells were sampled and were analyzed using standard methods. The trends of obtained data were analyzed during these years and the effects of different factors on the changes in electrical conductivity, concentration of chloride and total dissolved solids were clarified. The results showed that the amounts of some qualitative parameters have been increased during 10 years time which has led to decrease in water quality. The results also showed that increased in urban populations as well as extensive industrialization in the studied area are the most important reasons to influence underground water quality. Furthermore decrease in water quantity is also evident due to more water utilization and occurrence of recent droughts in the region during recent years.
Abstract: In this paper, we propose an approach for the classification of fingerprint databases. It is based on the fact that a fingerprint image is composed of regular texture regions that can be successfully represented by co-occurrence matrices. So, we first extract the features based on certain characteristics of the cooccurrence matrix and then we use these features to train a neural network for classifying fingerprints into four common classes. The obtained results compared with the existing approaches demonstrate the superior performance of our proposed approach.
Abstract: Locality Sensitive Hashing (LSH) is one of the most
promising techniques for solving nearest neighbour search problem in
high dimensional space. Euclidean LSH is the most popular variation
of LSH that has been successfully applied in many multimedia
applications. However, the Euclidean LSH presents limitations that
affect structure and query performances. The main limitation of the
Euclidean LSH is the large memory consumption. In order to achieve
a good accuracy, a large number of hash tables is required. In this
paper, we propose a new hashing algorithm to overcome the storage
space problem and improve query time, while keeping a good
accuracy as similar to that achieved by the original Euclidean LSH.
The Experimental results on a real large-scale dataset show that the
proposed approach achieves good performances and consumes less
memory than the Euclidean LSH.
Abstract: Combining classifiers is a useful method for solving
complex problems in machine learning. The ECOC (Error Correcting
Output Codes) method has been widely used for designing combining
classifiers with an emphasis on the diversity of classifiers. In this
paper, in contrast to the standard ECOC approach in which individual
classifiers are chosen homogeneously, classifiers are selected
according to the complexity of the corresponding binary problem. We
use SATIMAGE database (containing 6 classes) for our experiments.
The recognition error rate in our proposed method is %10.37 which
indicates a considerable improvement in comparison with the
conventional ECOC and stack generalization methods.
Abstract: Naive Bayes Nearest Neighbor (NBNN) and its variants, i,e., local NBNN and the NBNN kernels, are local feature-based classifiers that have achieved impressive performance in image classification. By exploiting instance-to-class (I2C) distances (instance means image/video in image/video classification), they avoid quantization errors of local image descriptors in the bag of words (BoW) model. However, the performances of NBNN, local NBNN and the NBNN kernels have not been validated on video analysis. In this paper, we introduce these three classifiers into human action recognition and conduct comprehensive experiments on the benchmark KTH and the realistic HMDB datasets. The results shows that those I2C based classifiers consistently outperform the SVM classifier with the BoW model.