Abstract: Neem is a highly heterozygous and commercially
important perennial plant. Conventionally, it is propagated by seeds
which loose viability within two weeks. Strictly cross pollinating
nature of the plant causes serious barrier to the genetic improvement
by conventional methods. Alternative methods of tree improvement
such as somatic hybridization, mutagenesis and genetic
transformation require an efficient in vitro plant regeneration system.
In this regard, somatic embryogenesis particularly secondary somatic
embryogenesis may offer an effective system for large scale plant
propagation without affecting the clonal fidelity of the regenerants. It
can be used for synthetic seed production, which further bolsters
conservation of this tree species which is otherwise very difficult
The present report describes the culture conditions necessary to
induce and maintain repetitive somatic embryogenesis, for the first
time, in neem. Out of various treatments tested, the somatic embryos
were induced directly from immature zygotic embryos of neem on
MS + TDZ (0.1 μM) + ABA (4 μM), in more than 76 % cultures.
Direct secondary somatic embryogenesis occurred from primary
somatic embryos on MS + IAA (5 μM) + GA3 (5 μM) in 12.5 %
cultures. Embryogenic competence of the explant as well as of the
primary embryos was maintained for a long period by repeated
subcultures at frequent intervals. A maximum of 10 % of these
somatic embryos were converted into plantlets.
Abstract: In this paper, we propose a side-peak cancellation
scheme for code acquisition of composite binary offset carrier
(CBOC) signals. We first model the family of CBOC signals in a
generic form, and then, propose a side-peak cancellation scheme
by combining correlation functions between the divided sub-carrier
and received signals. From numerical results, it is shown that the
proposed scheme removes the side-peak completely, and moreover,
the resulting correlation function demonstrates the better power ratio
performance than the CBOC autocorrelation.
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: The recommendation of the committee on corporate
governance for public companies in Nigeria, that the position of the
CEO be separated from board chair has generated serious debate
among scholars and practitioners. They have questioned the
appropriateness of implementing corporate governance model that is
based on Anglo-Saxon agency problem characterized by dispersed
ownership structure; where markets for corporate control, legal
regulation, and contractual incentives are the key governance
mechanisms. This paper strives to resolve the argument by adopting
an institutional perspective in testing the agency theory on board
duality. The study developed a theoretical and empirical model to
better understand how ownership structure influences agency conflict
and how such affects firm performance. Hence, the study examines
the relationship between CEO duality and firm performance using
two institutional ownership structures – dispersed ownership and
concentrated ownership structures. The empirical results show that
CEO duality is negatively correlated with firm performance in
Nigeria irrespective of the firm-s ownership structure. The findings
give credence to the recommendation of the Peterside Commission
on the need to separate the position of CEO from board chair.
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: Image registration plays an important role in the
diagnosis of dental pathologies such as dental caries, alveolar bone
loss and periapical lesions etc. This paper presents a new wavelet
based algorithm for registering noisy and poor contrast dental x-rays.
Proposed algorithm has two stages. First stage is a preprocessing
stage, removes the noise from the x-ray images. Gaussian filter has
been used. Second stage is a geometric transformation stage.
Proposed work uses two levels of affine transformation. Wavelet
coefficients are correlated instead of gray values. Algorithm has been
applied on number of pre and post RCT (Root canal treatment)
periapical radiographs. Root Mean Square Error (RMSE) and
Correlation coefficients (CC) are used for quantitative evaluation.
Proposed technique outperforms conventional Multiresolution
strategy based image registration technique and manual registration
technique.
Abstract: This paper presents a possibilistic (fuzzy) model in optimal siting and sizing of Distributed Generation (DG) for loss reduction and improve voltage profile in power distribution system. Multi-objective problem is developed in two phases. In the first one, the set of non-dominated planning solutions is obtained (with respect to the objective functions of fuzzy economic cost, and exposure) using genetic algorithm. In the second phase, one solution of the set of non-dominated solutions is selected as optimal solution, using a suitable max-min approach. This method can be determined operation-mode (PV or PQ) of DG. Because of considering load uncertainty in this paper, it can be obtained realistic results. The whole process of this method has been implemented in the MATLAB7 environment with technical and economic consideration for loss reduction and voltage profile improvement. Through numerical example the validity of the proposed method is verified.
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: A lot of matching algorithms with different characteristics have been introduced in recent years. For real time systems these algorithms are usually based on minutiae features. In this paper we introduce a novel approach for feature extraction in which the extracted features are independent of shift and rotation of the fingerprint and at the meantime the matching operation is performed much more easily and with higher speed and accuracy. In this new approach first for any fingerprint a reference point and a reference orientation is determined and then based on this information features are converted into polar coordinates. Due to high speed and accuracy of this approach and small volume of extracted features and easily execution of matching operation this approach is the most appropriate for real time applications.
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: The present research focus on the processing of mullite-based ceramics from oil refinery industrial wastes and byproducts of agricultural industry and on the investigating of silane modified surface of ceramics. Two waste products were used as initial material – waste aluminum oxide and waste rice husk. The burning - out additives used were waste rise husk. It is known that the oxide ceramics surface is hydrophilic due to the presence of – OH groups in it. The nature of ceramic surface regarding permeation of water and hydrocarbons can be changed by further treatment with silanes. The samples were studied mainly by X-ray analysis, FT-IR absorbance measurements and microscopic analysis. The X-ray analyses showed the phase composition depends on the firing temperature and on the purity of the starting alumina. Two kind of silanes were used for the transformation of surface from hydrophilic to hydrophobic – trimethoxymethylsilane (TMMS) and trimethylclorsilane (TMCS).
Abstract: Alpinia galanga is rhizome, generally known as
Greater galangal and is selected for isolation of newer constituents
accountable for various therapeutic activities. Present study is
intended to isolate glycoside from Alpinia galanga rhizomes. Alpinia
galanga methanolic extract was column chromatograph and eluted
with ethyl acetate-methanol (99:1) to isolate compound β-Sitosterol
Diarabinoside. Herein, the isolation and structural elucidation of new
compound is described. Chemical investigation of methanolic extract
of rhizomes of Alpinia galanga furnished a new compound β-
Sitosterol Diarabinoside. The IR, NMR and MASS investigations of
isolated compound confirmed its structure as β-Sitosterol
Diarabinoside, which is isolated for the first time from a medicinal
plant or any synthetic source.
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: This paper deals with the project selection problem. Project selection problem is one of the problems arose firstly in the field of operations research following some production concepts from primary product mix problem. Afterward, introduction of managerial considerations into the project selection problem have emerged qualitative factors and criteria to be regarded as well as quantitative ones. To overcome both kinds of criteria, an analytic network process is developed in this paper enhanced with fuzzy sets theory to tackle the vagueness of experts- comments to evaluate the alternatives. Additionally, a modified version of Least-Square method through a non-linear programming model is augmented to the developed group decision making structure in order to elicit the final weights from comparison matrices. Finally, a case study is considered by which developed structure in this paper is validated. Moreover, a sensitivity analysis is performed to validate the response of the model with respect to the condition alteration.
Abstract: A bird strike can cause damage to stationary and
rotating aircraft engine parts, especially the engine fan. This paper
presents a bird strike simulated by blocking four stator blade
passages. It includes the numerical results of the unsteady lowfrequency
aerodynamic forces and the aeroelastic behaviour caused
by a non-symmetric upstream flow affecting the first two rotor blade
stages in the axial-compressor of a jet engine. The obtained results
show that disturbances in the engine inlet strongly influence the level
of unsteady forces acting on the rotor blades. With a partially
blocked inlet the whole spectrum of low-frequency harmonics is
observed. Such harmonics can lead to rotor blade damage. The lowfrequency
amplitudes are higher in the first stage rotor blades than in
the second stage. In both rotor blades stages flutter appeared as a
result of bird strike.
Abstract: This paper proposes an efficient finite precision block floating point (BFP) treatment to the fixed coefficient finite impulse response (FIR) digital filter. The treatment includes effective implementation of all the three forms of the conventional FIR filters, namely, direct form, cascaded and par- allel, and a roundoff error analysis of them in the BFP format. An effective block formatting algorithm together with an adaptive scaling factor is pro- posed to make the realizations more simple from hardware view point. To this end, a generic relation between the tap weight vector length and the input block length is deduced. The implementation scheme also emphasises on a simple block exponent update technique to prevent overflow even during the block to block transition phase. The roundoff noise is also investigated along the analogous lines, taking into consideration these implementational issues. The simulation results show that the BFP roundoff errors depend on the sig- nal level almost in the same way as floating point roundoff noise, resulting in approximately constant signal to noise ratio over a relatively large dynamic range.
Abstract: This paper presents an online method that learns the
corresponding points of an object from un-annotated grayscale images
containing instances of the object. In the first image being
processed, an ensemble of node points is automatically selected
which is matched in the subsequent images. A Bayesian posterior
distribution for the locations of the nodes in the images is formed.
The likelihood is formed from Gabor responses and the prior assumes
the mean shape of the node ensemble to be similar in a translation
and scale free space. An association model is applied for separating
the object nodes and background nodes. The posterior distribution is
sampled with Sequential Monte Carlo method. The matched object
nodes are inferred to be the corresponding points of the object
instances. The results show that our system matches the object nodes
as accurately as other methods that train the model with annotated
training images.
Abstract: This study aims to specify to what extent students
understand topology during the lesson and to determine possible
misconceptions. 14 teacher trainees registered at Secondary School
Mathematics education department were observed in the topology
lessons throughout a semester and data collected at the first topology
lesson is presented here. Students- knowledge was evaluated using a
written test right before and after the topology lesson. Thus, what the
students learnt in terms of the definition and examples of topologic
space were specified as well as possible misconceptions. The
findings indicated that students did not fully comprehend the topic
and misunderstandings were due to insufficient pre-requisite
knowledge of abstract mathematical topics and mathematical
notation.
Abstract: Traffic incident has bad effect on all parts of society
so controlling road networks with enough traffic devices could help
to decrease number of accidents, so using the best method for
optimum site selection of these devices could help to implement good
monitoring system. This paper has considered here important criteria
for optimum site selection of traffic camera based on aggregation
methods such as Bagging and Dempster-Shafer concepts. In the first
step, important criteria such as annual traffic flow, distance from
critical places such as parks that need more traffic controlling were
identified for selection of important road links for traffic camera
installation, Then classification methods such as Artificial neural
network and Decision tree algorithms were employed for
classification of road links based on their importance for camera
installation. Then for improving the result of classifiers aggregation
methods such as Bagging and Dempster-Shafer theories were used.