Abstract: Avionic software architecture has transit from a
federated avionics architecture to an integrated modular avionics
(IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in
Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the
executable model have been brought up, however with less
consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic
interaction order sequence. In this paper, we proposed an
AADL-based model-driven design methodology to fulfill the purpose
to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the
mapping rules between the AADL653 elements and the elements in
Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our
approach. Finally, we give the related work and future research directions.
Abstract: This paper presents a new function expansion method for finding traveling wave solutions of a nonlinear equations and calls it the G G -expansion method, given by Wang et al recently. As an application of this new method, we study the well-known Sawada-Kotera-Kadomtsev-Petviashivili equation and Bogoyavlensky-Konoplechenko equation. With two new expansions, general types of soliton solutions and periodic solutions for these two equations are obtained.
Abstract: This work proposes an approach to address automatic
text summarization. This approach is a trainable summarizer, which
takes into account several features, including sentence position,
positive keyword, negative keyword, sentence centrality, sentence
resemblance to the title, sentence inclusion of name entity, sentence
inclusion of numerical data, sentence relative length, Bushy path of
the sentence and aggregated similarity for each sentence to generate
summaries. First we investigate the effect of each sentence feature on
the summarization task. Then we use all features score function to
train genetic algorithm (GA) and mathematical regression (MR)
models to obtain a suitable combination of feature weights. The
proposed approach performance is measured at several compression
rates on a data corpus composed of 100 English religious articles.
The results of the proposed approach are promising.
Abstract: A new approach is adopted in this paper based
on Turk and Pentland-s eigenface method. It was found that the
probability density function of the distance between the projection
vector of the input face image and the average projection vector of
the subject in the face database, follows Rayleigh distribution. In
order to decrease the false acceptance rate and increase the
recognition rate, the input face image has been recognized using two
thresholds including the acceptance threshold and the rejection
threshold. We also find out that the value of two thresholds will be
close to each other as number of trials increases. During the training,
in order to reduce the number of trials, the projection vectors for each
subject has been averaged. The recognition experiments using the
proposed algorithm show that the recognition rate achieves to
92.875% whilst the average number of judgment is only 2.56 times.
Abstract: Zirconium diamine and triamine complexes can possess biological activities. These complexes were synthesised via the reaction of equimolar quantities of 1,10-phenanthroline {NC3H3(C6H2)NC3H3} (L1) or 4-4-amino phenazone {ONC6H5(NH)CH(NH2} (L2) or diphenyl carbizon {HNNCO(NH)2(C6H5)} (L3) with a Zirconium Salt {ZrOCl2} in a 1:1 ratio to form complexes [{NC3H3(C6H2)NC3H3}ZrOCl2}] [ZrOCl2L1], [{(O2NC6H4(NH)(NH2)}ZrOCl2] [ZrOCl2L2] and [{HNNCO(NH)2(C6H5)ZrOCl2}] [ZrOCl2L3] respectively. They were characterised using Fourier Transform Infrared (FT-IR) and UV-Visible spectroscopy. Also a variable temperature study of these complexes was completed, using UV-Visible spectroscopy to observe electronic transitions under temperature control. Also a DFT study was done on these complexes via the information from FT-IR and UV-Visible spectroscopy.
These complexes were found to show different inhibition to the growth of bacterial strains of Bacillus spp. & Klebsiella spp. & E. coli & Proteus spp. & Pseudomona spp. at different concentrations (0.001, 0.2 and 1M). For better understanding these complexes were examined by using a Density Functional Theory (DFT) calculation.
Abstract: A direct adaptive controller for a class of unknown nonlinear discrete-time systems is presented in this article. The proposed controller is constructed by fuzzy rules emulated network (FREN). With its simple structure, the human knowledge about the plant is transferred to be if-then rules for setting the network. These adjustable parameters inside FREN are tuned by the learning mechanism with time varying step size or learning rate. The variation of learning rate is introduced by main theorem to improve the system performance and stabilization. Furthermore, the boundary of adjustable parameters is guaranteed through the on-line learning and membership functions properties. The validation of the theoretical findings is represented by some illustrated examples.
Abstract: In this paper a new fast simplification method is
presented. Such method realizes Karnough map with large
number of variables. In order to accelerate the operation of the
proposed method, a new approach for fast detection of group
of ones is presented. Such approach implemented in the
frequency domain. The search operation relies on performing
cross correlation in the frequency domain rather than time one.
It is proved mathematically and practically that the number of
computation steps required for the presented method is less
than that needed by conventional cross correlation. Simulation
results using MATLAB confirm the theoretical computations.
Furthermore, a powerful solution for realization of complex
functions is given. The simplified functions are implemented
by using a new desigen for neural networks. Neural networks
are used because they are fault tolerance and as a result they
can recognize signals even with noise or distortion. This is
very useful for logic functions used in data and computer
communications. Moreover, the implemented functions are
realized with minimum amount of components. This is done
by using modular neural nets (MNNs) that divide the input
space into several homogenous regions. Such approach is
applied to implement XOR function, 16 logic functions on one
bit level, and 2-bit digital multiplier. Compared to previous
non- modular designs, a clear reduction in the order of
computations and hardware requirements is achieved.
Abstract: In this paper a functional interpretation of quantum
theory (QT) with emphasis on quantum field theory (QFT) is proposed.
Besides the usual statements on relations between a functions
initial state and final state, a functional interpretation also contains
a description of the dynamic evolution of the function. That is, it
describes how things function. The proposed functional interpretation
of QT/QFT has been developed in the context of the author-s work
towards a computer model of QT with the goal of supporting
the largest possible scope of QT concepts. In the course of this
work, the author encountered a number of problems inherent in the
translation of quantum physics into a computer program. He came
to the conclusion that the goal of supporting the major QT concepts
can only be satisfied, if the present model of QT is supplemented
by a "functional interpretation" of QT/QFT. The paper describes a
proposal for that
Abstract: Neural networks are well known for their ability to
model non linear functions, but as statistical methods usually does,
they use a no parametric approach thus, a priori knowledge is not
obvious to be taken into account no more than the a posteriori
knowledge. In order to deal with these problematics, an original way
to encode the knowledge inside the architecture is proposed. This
method is applied to the problem of the evapotranspiration inside
karstic aquifer which is a problem of huge utility in order to deal
with water resource.
Abstract: This paper makes a detailed analysis regarding the definition of the intrinsic mode function and proves that Condition 1 of the intrinsic mode function can really be deduced from Condition 2. Finally, an improved definition of the intrinsic mode function is given.
Abstract: Estimation of runoff water quality parameters is required to determine appropriate water quality management options. Various models are used to estimate runoff water quality parameters. However, most models provide event-based estimates of water quality parameters for specific sites. The work presented in this paper describes the development of a model that continuously simulates the accumulation and wash-off of water quality pollutants in a catchment. The model allows estimation of pollutants build-up during dry periods and pollutants wash-off during storm events. The model was developed by integrating two individual models; rainfall-runoff model, and catchment water quality model. The rainfall-runoff model is based on the time-area runoff estimation method. The model allows users to estimate the time of concentration using a range of established methods. The model also allows estimation of the continuing runoff losses using any of the available estimation methods (i.e., constant, linearly varying or exponentially varying). Pollutants build-up in a catchment was represented by one of three pre-defined functions; power, exponential, or saturation. Similarly, pollutants wash-off was represented by one of three different functions; power, rating-curve, or exponential. The developed runoff water quality model was set-up to simulate the build-up and wash-off of total suspended solids (TSS), total phosphorus (TP) and total nitrogen (TN). The application of the model was demonstrated using available runoff and TSS field data from road and roof surfaces in the Gold Coast, Australia. The model provided excellent representation of the field data demonstrating the simplicity yet effectiveness of the proposed model.
Abstract: A triangular fin with variable fin base thickness is analyzed and optimized using a two-dimensional analytical method. The influence of fin base height and fin base thickness on the temperature in the fin is listed. For the fixed fin volumes, the maximum heat loss, the corresponding optimum fin effectiveness, fin base height and fin tip length as a function of the fin base thickness, convection characteristic number and dimensionless fin volume are represented. One of the results shows that the optimum heat loss increases whereas the corresponding optimum fin effectiveness decreases with the increase of fin volume.
Abstract: Script identification is one of the challenging steps in the development of optical character recognition system for bilingual or multilingual documents. In this paper an attempt is made for identification of English numerals at word level from Punjabi documents by using Gabor features. The support vector machine (SVM) classifier with five fold cross validation is used to classify the word images. The results obtained are quite encouraging. Average accuracy with RBF kernel, Polynomial and Linear Kernel functions comes out to be greater than 99%.
Abstract: The method of gait identification based on the nearest neighbor classification technique with motion similarity assessment by the dynamic time warping is proposed. The model based kinematic motion data, represented by the joints rotations coded by Euler angles and unit quaternions is used. The different pose distance functions in Euler angles and quaternion spaces are considered. To evaluate individual features of the subsequent joints movements during gait cycle, joint selection is carried out. To examine proposed approach database containing 353 gaits of 25 humans collected in motion capture laboratory is used. The obtained results are promising. The classifications, which takes into consideration all joints has accuracy over 91%. Only analysis of movements of hip joints allows to correctly identify gaits with almost 80% precision.
Abstract: In this paper, we use Radial Basis Function Networks
(RBFN) for solving the problem of environmental interference
cancellation of speech signal. We show that the Second Order Thin-
Plate Spline (SOTPS) kernel cancels the interferences effectively.
For make comparison, we test our experiments on two conventional
most used RBFN kernels: the Gaussian and First order TPS (FOTPS)
basis functions. The speech signals used here were taken from the
OGI Multi-Language Telephone Speech Corpus database and were
corrupted with six type of environmental noise from NOISEX-92
database. Experimental results show that the SOTPS kernel can
considerably outperform the Gaussian and FOTPS functions on
speech interference cancellation problem.
Abstract: This paper presents a longitudinal quasi-linear model for the ADMIRE model. The ADMIRE model is a nonlinear model of aircraft flying in the condition of high angle of attack. So it can-t be considered to be a linear system approximately. In this paper, for getting the longitudinal quasi-linear model of the ADMIRE, a state transformation based on differentiable functions of the nonscheduling states and control inputs is performed, with the goal of removing any nonlinear terms not dependent on the scheduling parameter. Since it needn-t linear approximation and can obtain the exact transformations of the nonlinear states, the above-mentioned approach is thought to be appropriate to establish the mathematical model of ADMIRE. To verify this conclusion, simulation experiments are done. And the result shows that this quasi-linear model is accurate enough.
Abstract: Bloom filter is a probabilistic and memory efficient
data structure designed to answer rapidly whether an element is
present in a set. It tells that the element is definitely not in the set but
its presence is with certain probability. The trade-off to use Bloom
filter is a certain configurable risk of false positives. The odds of a
false positive can be made very low if the number of hash function is
sufficiently large. For spam detection, weight is attached to each set
of elements. The spam weight for a word is a measure used to rate the
e-mail. Each word is assigned to a Bloom filter based on its weight.
The proposed work introduces an enhanced concept in Bloom filter
called Bin Bloom Filter (BBF). The performance of BBF over
conventional Bloom filter is evaluated under various optimization
techniques. Real time data set and synthetic data sets are used for
experimental analysis and the results are demonstrated for bin sizes 4,
5, 6 and 7. Finally analyzing the results, it is found that the BBF
which uses heuristic techniques performs better than the traditional
Bloom filter in spam detection.
Abstract: Impurity metals such as manganese and cadmium
from high-tenor cobalt electrolyte solution were selectively removed
by solvent extraction method using Co-D2EHPA after converting the functional group of D2EHPA with Co2+ ions. The process parameters
such as pH, organic concentration, O/A ratio, kinetics etc. were
investigated and the experiments were conducted by batch tests in the laboratory bench scale. Results showed that a significant amount
of manganese and cadmium can be extracted using Co-D2EHPA for the optimum processing of cobalt electrolyte solution at equilibrium pH about 3.5. The McCabe-Thiele diagram, constructed from the
extraction studies showed that 100% impurities can be extracted through four stages for manganese and three stages for cadmium
using O/A ratio of 0.65 and 1.0, respectively. From the stripping study, it was found that 100% manganese and cadmium can be stripped from the loaded organic using 0.4 M H2SO4 in a single
contact. The loading capacity of Co-D2EHPA by manganese and cadmium were also investigated with different O/A ratio as well as
with number of stages of contact of aqueous and organic phases. Valuable information was obtained for the designing of an impurities
removal process for the production of pure cobalt with less trouble in the electrowinning circuit.
Abstract: The angular distribution of Compton scattering of two
quanta originating in the annihilation of a positron with an electron
is investigated as a quantum key distribution (QKD) mechanism in
the gamma spectral range. The geometry of coincident Compton
scattering is observed on the two sides as a way to obtain partially
correlated readings on the quantum channel. We derive the noise
probability density function of a conceptually equivalent prepare
and measure quantum channel in order to evaluate the limits of the
concept in terms of the device secrecy capacity and estimate it at
roughly 1.9 bits per 1 000 annihilation events. The high error rate
is well above the tolerable error rates of the common reconciliation
protocols; therefore, the proposed key agreement protocol by public
discussion requires key reconciliation using classical error-correcting
codes. We constructed a prototype device based on the readily
available monolithic detectors in the least complex setup.
Abstract: In this paper, we combine a probabilistic neural method with radial-bias functions in order to construct the lithofacies of the wells DF01, DF02 and DF03 situated in the Triassic province of Algeria (Sahara). Lithofacies is a crucial problem in reservoir characterization. Our objective is to facilitate the experts' work in geological domain and to allow them to obtain quickly the structure and the nature of lands around the drilling. This study intends to design a tool that helps automatic deduction from numerical data. We used a probabilistic formalism to enhance the classification process initiated by a Self-Organized Map procedure. Our system gives lithofacies, from well-log data, of the concerned reservoir wells in an aspect easy to read by a geology expert who identifies the potential for oil production at a given source and so forms the basis for estimating the financial returns and economic benefits.