Abstract: In this paper, novel techniques in increasing the accuracy
and speed of convergence of a Feed forward Back propagation
Artificial Neural Network (FFBPNN) with polynomial activation
function reported in literature is presented. These technique was
subsequently used to determine the coefficients of Autoregressive
Moving Average (ARMA) and Autoregressive (AR) system. The
results obtained by introducing sequential and batch method of weight
initialization, batch method of weight and coefficient update, adaptive
momentum and learning rate technique gives more accurate result
and significant reduction in convergence time when compared t the
traditional method of back propagation algorithm, thereby making
FFBPNN an appropriate technique for online ARMA coefficient
determination.
Abstract: As wireless sensor networks are energy constraint networks
so energy efficiency of sensor nodes is the main design issue.
Clustering of nodes is an energy efficient approach. It prolongs the
lifetime of wireless sensor networks by avoiding long distance communication.
Clustering algorithms operate in rounds. Performance of
clustering algorithm depends upon the round time. A large round
time consumes more energy of cluster heads while a small round
time causes frequent re-clustering. So existing clustering algorithms
apply a trade off to round time and calculate it from the initial
parameters of networks. But it is not appropriate to use initial
parameters based round time value throughout the network lifetime
because wireless sensor networks are dynamic in nature (nodes can be
added to the network or some nodes go out of energy). In this paper
a variable round time approach is proposed that calculates round
time depending upon the number of active nodes remaining in the
field. The proposed approach makes the clustering algorithm adaptive
to network dynamics. For simulation the approach is implemented
with LEACH in NS-2 and the results show that there is 6% increase
in network lifetime, 7% increase in 50% node death time and 5%
improvement over the data units gathered at the base station.
Abstract: Deep cold rolling (DCR) and low plasticity burnishing (LPB) process are cold working processes, which easily produce a smooth and work-hardened surface by plastic deformation of surface irregularities. The present study focuses on the surface roughness and surface hardness aspects of AISI 4140 work material, using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in order to identify the predominant factors amongst the selected parameters. They were then categorized in order of significance followed by setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. In the present work, the influence of main process parameters (force, feed rate, number of tool passes/overruns, initial roughness of the work piece, ball material, ball diameter and lubricant used) on the surface roughness and the hardness of AISI 4140 steel were studied for both LPB and DCR process and the results are compared. It was observed that by using LPB process surface hardness has been improved by 167% and in DCR process surface hardness has been improved by 442%. It was also found that the force, ball diameter, number of tool passes and initial roughness of the workpiece are the most pronounced parameters, which has a significant effect on the work piece-s surface during deep cold rolling and low plasticity burnishing process.
Abstract: In this paper, a clustering algorithm named KHarmonic
means (KHM) was employed in the training of Radial
Basis Function Networks (RBFNs). KHM organized the data in
clusters and determined the centres of the basis function. The popular
clustering algorithms, namely K-means (KM) and Fuzzy c-means
(FCM), are highly dependent on the initial identification of elements
that represent the cluster well. In KHM, the problem can be avoided.
This leads to improvement in the classification performance when
compared to other clustering algorithms. A comparison of the
classification accuracy was performed between KM, FCM and KHM.
The classification performance is based on the benchmark data sets:
Iris Plant, Diabetes and Breast Cancer. RBFN training with the KHM
algorithm shows better accuracy in classification problem.
Abstract: We consider the development of an eight order Adam-s
type method, with A-stability property discussed by expressing them
as a one-step method in higher dimension. This makes it suitable
for solving variety of initial-value problems. The main method and
additional methods are obtained from the same continuous scheme
derived via interpolation and collocation procedures. The methods
are then applied in block form as simultaneous numerical integrators
over non-overlapping intervals. Numerical results obtained using the
proposed block form reveals that it is highly competitive with existing
methods in the literature.
Abstract: Linear stability of wake-shear layers in two-phase
shallow flows is analyzed in the present paper. Stability analysis is
based on two-dimensional shallow water equations. It is assumed that
the fluid contains uniformly distributed solid particles. No dynamic
interaction between the carrier fluid and particles is expected in the
initial moment. Linear stability curves are obtained for different
values of the particle loading parameter, the velocity ratio and the
velocity deficit. It is shown that the increase in the velocity ratio
destabilizes the flow. The particle loading parameter has a stabilizing
effect on the flow. The role of the velocity deficit is also
destabilizing: the increase of the velocity deficit leads to less stable
flow.
Abstract: This paper proposes an efficient lattice-reduction-aided
detection (LRD) scheme to improve the detection performance of
MIMO-OFDM system. In this proposed scheme, V candidate symbols
are considered at the first layer, and V probable streams are
detected with LRD scheme according to the first detected V candidate
symbols. Then, the most probable stream is selected through a ML
test. Since the proposed scheme can more accurately detect initial
symbol and can reduce transmission of error to rest symbols, the
proposed scheme shows more improved performance than conventional
LRD with very low complexity.
Abstract: A study was carried out at the Rice Research Institute of Iran (RRII) to investigate the effect of rollers differential peripheral speed of commercial rubber roll husker and paddy moisture content on the husking index and percentage of broken rice. The experiment was conducted at six levels of rollers differential speed (1.5, 2.2, 2.9, 3.6, 4.3 and 5 m/s) and three levels of paddy moisture content (8-9, 10-11 and 12-13% w.b.). Two common paddy varieties namely, Binam and Khazer, were selected for this study. Results revealed that the effect of rollers differential speed and moisture content significantly (P
Abstract: A full six degrees of freedom (6-DOF) flight dynamics
model is proposed for the accurate prediction of short and long-range
trajectories of high spin and fin-stabilized projectiles via atmospheric
flight to final impact point. The projectiles is assumed to be both rigid
(non-flexible), and rotationally symmetric about its spin axis launched
at low and high pitch angles. The mathematical model is based on the
full equations of motion set up in the no-roll body reference frame and
is integrated numerically from given initial conditions at the firing
site. The projectiles maneuvering motion depends on the most
significant force and moment variations, in addition to wind and
gravity. The computational flight analysis takes into consideration the
Mach number and total angle of attack effects by means of the
variable aerodynamic coefficients. For the purposes of the present
work, linear interpolation has been applied from the tabulated database
of McCoy-s book. The developed computational method gives
satisfactory agreement with published data of verified experiments and
computational codes on atmospheric projectile trajectory analysis for
various initial firing flight conditions.
Abstract: A clustering based technique has been developed and implemented for Short Term Load Forecasting, in this article. Formulation has been done using Mean Absolute Percentage Error (MAPE) as an objective function. Data Matrix and cluster size are optimization variables. Model designed, uses two temperature variables. This is compared with six input Radial Basis Function Neural Network (RBFNN) and Fuzzy Inference Neural Network (FINN) for the data of the same system, for same time period. The fuzzy inference system has the network structure and the training procedure of a neural network which initially creates a rule base from existing historical load data. It is observed that the proposed clustering based model is giving better forecasting accuracy as compared to the other two methods. Test results also indicate that the RBFNN can forecast future loads with accuracy comparable to that of proposed method, where as the training time required in the case of FINN is much less.
Abstract: Radio Frequency Identification (RFID) initially introduced
during WW-II, has revolutionized the world with its numerous
benefits and plethora of implementations in diverse areas ranging
from manufacturing to agriculture to healthcare to hotel management.
This work reviews the current research in this area with emphasis
on applications for supply chain management and to develop a
taxonomic framework to classify literature which will enable swift
and easy content analysis and also help identify areas for future
research.
Abstract: The adsorption of simulated aqueous solution containing textile remazol reactive dye, namely Red 3BS by palm shell activated carbon (PSAC) as adsorbent was carried out using Response Surface Methodology (RSM). A Box-Behnken design in three most important operating variables; initial dye concentration, dosage of adsorbent and speed of impeller was employed for experimental design and optimization of results. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95% confidence limits. Model indicated that with the increasing of dosage and speed give the result of removal up to 90% with the capacity uptake more than 7 mg/g. High regression coefficient between the variables and the response (R-Sq = 93.9%) showed of good evaluation of experimental data by polynomial regression model.
Abstract: This paper addresses one important aspect of
combustion system analysis, the spray evaporation and
dispersion modeling. In this study we assume an empty
cylinder which is as a simulator for a ramjet engine and the
cylinder has been studied by cold flow. Four nozzles have the
duties of injection which are located in the entrance of
cylinder. The air flow comes into the cylinder from one side
and injection operation will be done. By changing injection
velocity and entrance air flow velocity, we have studied
droplet sizing and efficient mass fraction of fuel vapor near
and at the exit area. We named the mass of fuel vapor inside
the flammability limit as the efficient mass fraction. Further,
we decreased the initial temperature of fuel droplets and we
have repeated the investigating again. To fulfill the calculation
we used a modified version of KIVA-3V.
Abstract: State-dependent Riccati equation based controllers are
becoming increasingly popular because of having attractive
properties like optimality, stability and robustness. This paper focuses
on the design of a roll autopilot for a fin stabilized and canard
controlled 122mm artillery rocket using state-dependent Riccati
equation technique. Initial spin is imparted to rocket during launch
and it quickly decays due to straight tail fins. After the spin phase, the
roll orientation of rocket is brought to zero with the canard deflection
commands generated by the roll autopilot. Roll autopilot has been
developed by considering uncoupled roll, pitch and yaw channels.
The canard actuator is modeled as a second-order nonlinear system.
Elements of the state weighing matrix for Riccati equation have been
chosen to be state dependent to exploit the design flexibility offered
by the Riccati equation technique. Simulation results under varying
conditions of flight demonstrate the wide operating range of the
proposed autopilot.
Abstract: Adsorption of Toluidine blue dye from aqueous solutions onto Neem Leaf Powder (NLP) has been investigated. The surface characterization of this natural material was examined by Particle size analysis, Scanning Electron Microscopy (SEM), Fourier Transform Infrared (FTIR) spectroscopy and X-Ray Diffraction (XRD). The effects of process parameters such as initial concentration, pH, temperature and contact duration on the adsorption capacities have been evaluated, in which pH has been found to be most effective parameter among all. The data were analyzed using the Langmuir and Freundlich for explaining the equilibrium characteristics of adsorption. And kinetic models like pseudo first- order, second-order model and Elovich equation were utilized to describe the kinetic data. The experimental data were well fitted with Langmuir adsorption isotherm model and pseudo second order kinetic model. The thermodynamic parameters, such as Free energy of adsorption (AG"), enthalpy change (AH') and entropy change (AS°) were also determined and evaluated.
Abstract: The recent developments in computing and
communication technology permit to users to access multimedia
documents with variety of devices (PCs, PDAs, mobile phones...)
having heterogeneous capabilities. This diversification of supports
has trained the need to adapt multimedia documents according to
their execution contexts. A semantic framework for multimedia
document adaptation based on the conceptual neighborhood graphs
was proposed. In this framework, adapting consists on finding
another specification that satisfies the target constraints and which is
as close as possible from the initial document. In this paper, we
propose a new way of building the conceptual neighborhood graphs
to best preserve the proximity between the adapted and the original
documents and to deal with more elaborated relations models by
integrating the relations relaxation graphs that permit to handle the
delays and the distances defined within the relations.
Abstract: A frictionless contact problem for a two-layer orthotropic elastic medium loaded through a rigid flat stamp is considered. It is assumed that tensile tractions are not allowed and only compressive tractions can be transmitted across the interface. In the solution, effect of gravity is taken into consideration. If the external load on the rigid stamp is less than or equal to a critical value, continuous contact between the layers is maintained. The problem is expressed in terms of a singular integral equation by using the theory of elasticity and the Fourier transforms. Numerical results for initial separation point, critical separation load and contact stress distribution are presented.
Abstract: The relics of traditional folk culture in Kazakhstan are ceremonies or their fragments - such as weddings, funerals, shamanism. The world of spiritual creatures, spirits-protectors, spirits-helpers, injury spirits, spirits of illnesses, etc., is described in detail in shamanic rites (in Kazakh culture it is called bakslyk). The study of these displays of folk culture, which reflect the peoples` ethnic mentality or notions about the structure, values and hierarchies of the universe, includes collection and recording of the field materials and their interpretation, i.e. reconstruction of those meanings which were initially embodied or “coded" in folklore. A distinctive feature of Kazakh nomadic culture is its self-preservation and actualization, almost untouched the ancient mythologies of the world, in particular, the mythologies connected with music, musical instruments and the creator of music. Within the frameworks of the traditional culture the word and the music keep the sacral meaning. The ritual melodies and what they carry – the holly, and at the same time unexplored, powerful and threatening, uncontrolled by people world – keep on attributing the soul to all, connected with culture.
Abstract: Initial values of reference vectors have significant influence on recognition accuracy in LVQ. There are several existing techniques, such as SOM and k-means, for setting initial values of reference vectors, each of which has provided some positive results. However, those results are not sufficient for the improvement of recognition accuracy. This study proposes an ACO-used method for initializing reference vectors with an aim to achieve recognition accuracy higher than those obtained through conventional methods. Moreover, we will demonstrate the effectiveness of the proposed method by applying it to the wine data and English vowel data and comparing its results with those of conventional methods.
Abstract: A hybrid feature based adaptive particle filter algorithm is presented for object tracking in real scenarios with static camera.
The hybrid feature is combined by two effective features: the Grayscale Arranging Pairs (GAP) feature and the color histogram feature. The GAP feature has high discriminative ability even under conditions of severe illumination variation and dynamic background
elements, while the color histogram feature has high reliability to identify the detected objects. The combination of two features covers the shortage of single feature. Furthermore, we adopt an updating
target model so that some external problems such as visual angles can be overcame well. An automatic initialization algorithm is introduced which provides precise initial positions of objects. The experimental
results show the good performance of the proposed method.