Abstract: In this paper, estimation of the linear regression
model is made by ordinary least squares method and the
partially linear regression model is estimated by penalized
least squares method using smoothing spline. Then, it is
investigated that differences and similarity in the sum of
squares related for linear regression and partial linear
regression models (semi-parametric regression models). It is
denoted that the sum of squares in linear regression is reduced
to sum of squares in partial linear regression models.
Furthermore, we indicated that various sums of squares in the
linear regression are similar to different deviance statements in
partial linear regression. In addition to, coefficient of the
determination derived in linear regression model is easily
generalized to coefficient of the determination of the partial
linear regression model. For this aim, it is made two different
applications. A simulated and a real data set are considered to
prove the claim mentioned here. In this way, this study is
supported with a simulation and a real data example.
Abstract: The Goursat partial differential equation arises in
linear and non linear partial differential equations with mixed
derivatives. This equation is a second order hyperbolic partial
differential equation which occurs in various fields of study such as
in engineering, physics, and applied mathematics. There are many
approaches that have been suggested to approximate the solution of
the Goursat partial differential equation. However, all of the
suggested methods traditionally focused on numerical differentiation
approaches including forward and central differences in deriving the
scheme. An innovation has been done in deriving the Goursat partial
differential equation scheme which involves numerical integration
techniques. In this paper we have developed a new scheme to solve
the Goursat partial differential equation based on the Adomian
decomposition (ADM) and associated with Boole-s integration rule to
approximate the integration terms. The new scheme can easily be
applied to many linear and non linear Goursat partial differential
equations and is capable to reduce the size of computational work.
The accuracy of the results reveals the advantage of this new scheme
over existing numerical method.
Abstract: Cutting fluids, usually in the form of a liquid, are
applied to the chip formation zone in order to improve the cutting
conditions. Cutting fluid can be expensive and represents a biological
and environmental hazard that requires proper recycling and
disposal, thus adding to the cost of the machining operation. For
these reasons dry cutting or dry machining has become an
increasingly important approach; in dry machining no coolant or
lubricant is used. This paper discussed the effect of the dry cutting on
cutting force and tool life when machining aerospace materials
(Haynes 242) with using two different coated carbide cutting tools
(TiAlN and TiN/MT-TiCN/TiN). Response surface method (RSM)
was used to minimize the number of experiments. ParTiAlN Swarm
Optimisation (PSO) models were developed to optimize the
machining parameters (cutting speed, federate and axial depth) and
obtain the optimum cutting force and tool life. It observed that
carbide cutting tool coated with TiAlN performed better in dry
cutting compared with TiN/MT-TiCN/TiN. On other hand, TiAlN
performed more superior with using of 100 % water soluble coolant.
Due to the high temperature produced by aerospace materials, the
cutting tool still required lubricant to sustain the heat transfer from
the workpiece.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: This research uses computational linguistics, an area of study that employs a computer to process natural language, and aims at discerning the patterns that exist in declarative sentences used in technical texts. The approach is mathematical, and the focus is on instructional texts found on web pages. The technique developed by the author and named the MAYA Semantic Technique is used here and organized into four stages. In the first stage, the parts of speech in each sentence are identified. In the second stage, the subject of the sentence is determined. In the third stage, MAYA performs a frequency analysis on the remaining words to determine the verb and its object. In the fourth stage, MAYA does statistical analysis to determine the content of the web page. The advantage of the MAYA Semantic Technique lies in its use of mathematical principles to represent grammatical operations which assist processing and accuracy if performed on unambiguous text. The MAYA Semantic Technique is part of a proposed architecture for an entire web-based intelligent tutoring system. On a sample set of sentences, partial semantics derived using the MAYA Semantic Technique were approximately 80% accurate. The system currently processes technical text in one domain, namely Cµ programming. In this domain all the keywords and programming concepts are known and understood.
Abstract: This article describes a Web pages automatic filtering system. It is an open and dynamic system based on multi agents architecture. This system is built up by a set of agents having each a quite precise filtering task of to carry out (filtering process broken up into several elementary treatments working each one a partial solution). New criteria can be added to the system without stopping its execution or modifying its environment. We want to show applicability and adaptability of the multi-agents approach to the networks information automatic filtering. In practice, most of existing filtering systems are based on modular conception approaches which are limited to centralized applications which role is to resolve static data flow problems. Web pages filtering systems are characterized by a data flow which varies dynamically.
Abstract: Unsteady natural convection and heat transfer in a square cavity partially filled with porous media using a thermal
non-equilibrium model is studied in this paper. The left vertical wall is
maintained at a constant hot temperature Th and the right vertical wall
is maintained at a constant cold temperature Tc, while the horizontal
walls are adiabatic. The governing equations are obtained by applying
the Darcy model and Boussinesq approximation. COMSOL’s finite
element method is used to solve the non-dimensional governing
equations together with specified boundary conditions. The governing
parameters of this study are the Rayleigh number (Ra = 10^5, and Ra = 10^6 ), Darcy namber (Da = 10^−2, and Da = 10^−3),
the modified thermal conductivity ratio (10^−1 ≤ γ ≤ 10^4), the inter-phase heat transfer coefficien (10^−1 ≤ H ≤ 10^3) and the
time dependent (0.001 ≤ τ ≤ 0.2). The results presented for
values of the governing parameters in terms of streamlines in both
fluid/porous-layer, isotherms of fluid in fluid/porous-layer, isotherms
of solid in porous layer, and average Nusselt number.
Abstract: The aim of this paper is to rank the impact of Object
Oriented(OO) metrics in fault prediction modeling using Artificial
Neural Networks(ANNs). Past studies on empirical validation of
object oriented metrics as fault predictors using ANNs have focused
on the predictive quality of neural networks versus standard
statistical techniques. In this empirical study we turn our attention to
the capability of ANNs in ranking the impact of these explanatory
metrics on fault proneness. In ANNs data analysis approach, there is
no clear method of ranking the impact of individual metrics. Five
ANN based techniques are studied which rank object oriented
metrics in predicting fault proneness of classes. These techniques are
i) overall connection weights method ii) Garson-s method iii) The
partial derivatives methods iv) The Input Perturb method v) the
classical stepwise methods. We develop and evaluate different
prediction models based on the ranking of the metrics by the
individual techniques. The models based on overall connection
weights and partial derivatives methods have been found to be most
accurate.
Abstract: This study investigates CO2 mitigation by methanol
synthesis from flue gas CO2 and H2 generation through water
electrolysis. Electrolytic hydrogen generation is viable provided that
the required electrical power is supplied from renewable energy
resources; whereby power generation from renewable resources is yet
commercial challenging. This approach contribute to zero-emission,
moreover it produce oxygen which could be used as feedstock for
chemical process. At ZPC, however, oxygen would be utilized
through partial oxidation of methane in autothermal reactor (ATR);
this makes ease the difficulties of O2 delivery and marketing. On the
other hand, onboard hydrogen storage and consumption; in methanol
plant; make the project economically more competitive.
Abstract: We propose a control design scheme that aims to
prevent undesirable liquid outpouring and suppress sloshing during
the forward and backward tilting phases of the pouring process, for
the case of liquid containers carried by manipulators. The proposed
scheme combines a partial inverse dynamics controller with a PID
controller, tuned with the use of a “metaheuristic" search algorithm.
The “metaheuristic" search algorithm tunes the PID controller based
on simulation results of the plant-s linearization around the operating
point corresponding to the critical tilting angle, where outpouring
initiates. Liquid motion is modeled using the well-known pendulumtype
model. However, the proposed controller does not require
measurements of the liquid-s motion within the tank.
Abstract: This paper presents the results of an experimental
investigation carried out to evaluate the shrinkage of High Strength
Concrete. High Strength Concrete is made by partially replacement of
cement by flyash and silica fume. The shrinkage of High Strength
Concrete has been studied using the different types of coarse and fine
aggregates i.e. Sandstone and Granite of 12.5 mm size and Yamuna
and Badarpur Sand. The Mix proportion of concrete is 1:0.8:2.2 with
water cement ratio as 0.30. Superplasticizer dose @ of 2% by weight
of cement is added to achieve the required degree of workability in
terms of compaction factor.
From the test results of the above investigation it can be concluded
that the shrinkage strain of High Strength Concrete increases with
age. The shrinkage strain of concrete with replacement of cement by
10% of Flyash and Silica fume respectively at various ages are more
(6 to 10%) than the shrinkage strain of concrete without Flyash and
Silica fume. The shrinkage strain of concrete with Badarpur sand as
Fine aggregate at 90 days is slightly less (10%) than that of concrete
with Yamuna Sand. Further, the shrinkage strain of concrete with
Granite as Coarse aggregate at 90 days is slightly less (6 to 7%) than
that of concrete with Sand stone as aggregate of same size. The
shrinkage strain of High Strength Concrete is also compared with that
of normal strength concrete. Test results show that the shrinkage
strain of high strength concrete is less than that of normal strength
concrete.
Abstract: This article provides partial evaluation index and its
standard of sports aerobics, including the following 12 indexes: health
vitality, coordination, flexibility, accuracy, pace, endurance, elasticity,
self-confidence, form, control, uniformity and musicality. The
three-layer BP artificial neural network model including input layer,
hidden layer and output layer is established. The result shows that the
model can well reflect the non-linear relationship between the
performance of 12 indexes and the overall performance. The predicted
value of each sample is very close to the true value, with a relative
error fluctuating around of 5%, and the network training is successful.
It shows that BP network has high prediction accuracy and good
generalization capacity if being applied in sports aerobics performance
evaluation after effective training.
Abstract: In this paper, the two-dimension differential transformation method (DTM) is employed to obtain the closed form solutions of the three famous coupled partial differential equation with physical interest namely, the coupled Korteweg-de Vries(KdV) equations, the coupled Burgers equations and coupled nonlinear Schrödinger equation. We begin by showing that how the differential transformation method applies to a linear and non-linear part of any PDEs and apply on these coupled PDEs to illustrate the sufficiency of the method for this kind of nonlinear differential equations. The results obtained are in good agreement with the exact solution. These results show that the technique introduced here is accurate and easy to apply.
Abstract: Nonlinear propagation of ion-acoustic waves in a selfgravitating
dusty plasma consisting of warm positive ions,
isothermal two-temperature electrons and negatively charged dust
particles having charge fluctuations is studied using the reductive
perturbation method. It is shown that the nonlinear propagation of
ion-acoustic waves in such plasma can be described by an uncoupled
third order partial differential equation which is a modified form of
the usual Korteweg-deVries (KdV) equation. From this nonlinear
equation, a new type of solution for the ion-acoustic wave is
obtained. The effects of two-temperature electrons, gravity and dust
charge fluctuations on the ion-acoustic solitary waves are discussed
with possible applications.
Abstract: Annotation of a protein sequence is pivotal for the understanding of its function. Accuracy of manual annotation provided by curators is still questionable by having lesser evidence strength and yet a hard task and time consuming. A number of computational methods including tools have been developed to tackle this challenging task. However, they require high-cost hardware, are difficult to be setup by the bioscientists, or depend on time intensive and blind sequence similarity search like Basic Local Alignment Search Tool. This paper introduces a new method of assigning highly correlated Gene Ontology terms of annotated protein sequences to partially annotated or newly discovered protein sequences. This method is fully based on Gene Ontology data and annotations. Two problems had been identified to achieve this method. The first problem relates to splitting the single monolithic Gene Ontology RDF/XML file into a set of smaller files that can be easy to assess and process. Thus, these files can be enriched with protein sequences and Inferred from Electronic Annotation evidence associations. The second problem involves searching for a set of semantically similar Gene Ontology terms to a given query. The details of macro and micro problems involved and their solutions including objective of this study are described. This paper also describes the protein sequence annotation and the Gene Ontology. The methodology of this study and Gene Ontology based protein sequence annotation tool namely extended UTMGO is presented. Furthermore, its basic version which is a Gene Ontology browser that is based on semantic similarity search is also introduced.
Abstract: Importance of environmental efficiency of electric power industry stems from high demand for energy combined with global warming concerns. It is especially essential for the world largest economies like that of the United States. The paper introduces a Data Envelopment Analysis (DEA) model of environmental efficiency using indicators of fossil fuels utilization, emissions rate, and electric power losses. Using DEA is advantageous in this situation over other approaches due to its nonparametric nature. The paper analyzes data for the period of 1990 - 2006 by comparing actual yearly levels in each dimension with the best values of partial indicators for the period. As positive factors of efficiency, tendency to the decline in emissions rates starting 2000, and in electric power losses starting 2004 may be mentioned together with increasing trend of fuel utilization starting 1999. As a result, dynamics of environmental efficiency is positive starting 2002. The main concern is the decline in fossil fuels utilization in 2006. This negative change should be reversed to comply with ecological and economic requirements.
Abstract: Measurements of capacitance C and dissipation
factor tand of the stator insulation system provide useful information
about internal defects within the insulation. The index k is defined as
the proportionality constant between the changes at high voltage of
capacitance DC and of the dissipation factor Dtand . DC and
Dtand values were highly correlated when small flat defects were
within the insulation and that correlation was lost in the presence of
large narrow defects like electrical treeing. The discrimination
between small and large defects is made resorting to partial discharge
PD phase angle analysis. For the validation of the results, C and tand
measurements were carried out in a 15MVA 4160V steam turbine
turbogenerator placed in a sugar mill. In addition, laboratory test
results obtained by other authors were analyzed jointly. In such
laboratory tests, model coil bars subjected to thermal cycling resulted
highly degraded and DC and Dtand values were not correlated. Thus,
the index k could not be calculated.
Abstract: In mobile computing environments, there are many
new non existing problems in the distributed system, which is
consisted of stationary hosts because of host mobility, sudden
disconnection by handoff in wireless networks, voluntary
disconnection for efficient power consumption of a mobile host, etc.
To solve the problems, we proposed the architecture of Partial
Connection Manager (PCM) in this paper. PCM creates the limited
number of mobile agents according to priority, sends them in parallel
to servers, and combines the results to process the user request rapidly.
In applying the proposed PCM to the mobile market agent service, we
understand that the mobile agent technique could be suited for the
mobile computing environment and the partial connection problem
management.
Abstract: In conventional seedling production, the seedlings are
being grown in the open field under natural conditions. Here they are
susceptible to sudden changes in climate were their quality and yield
is affected. Quality seedlings are essential for good growth and
performance of crops in main field; they serve as a foundation for the
economic returns to the farmer. Producing quality seedling demands
usage of hybrid seeds as they have the ability to result in better yield,
greater uniformity, improved color, disease resistance, and so forth.
Hybrid seed production poses major operational challenge and its
seed use efficiency plays an important role. Thus in order to
overcome the difficulties currently present in conventional seedling
production and to efficiently use hybrid seeds, ITC Limited Agri
Business Divisions - Sustainability Cell as conceptualized a novel
method of seedling production unit for farmers in West Godavari
District of Andhra Pradesh. The “Green House based Float Seedling"
methodology aims at a protected cultivation technique wherein the
micro climate surrounding the plant/seedling body is controlled
partially or fully as per the requirement of the species. This paper
reports on the techno economic evaluation of green house for
cultivation of float based seedling production with experimental
results that was attained from the pilot implementation in West
Godavari District, Rajahmundry region of India.
Abstract: The phylogenetic analysis using the most conservative
portions of 18S rRNA gene revealed the phylogenetic relationship
among the two populations where DNA divergence showed that the
nucleotides diversity value were -0.00838 for the Tanjung Dawai,
Kedah and -0.00708 for the Cherating, Pahang populations
respectively. The net nucleotide divergence among populations (Da)
was -0.0073 indicating a low polymorphism among the populations
studied. Total number of mutations in the Tanjung Dawai, Kedah
samples was higher than Cherating, Pahang samples, which are 73 and
59 respectively while shared mutations across the populations were 8,
and reveal the evolutionary in the genome of Malaysian T. gigas. The
tree topology of both populations inferred using Neigbour-joining
method by comparing 1791 bp of partial 18S rRNA sequence revealed
that T. gigas haplotypes were clustered into seven clades, suggesting
that they are genetically diverse among populations which derived
from a common ancestor.