Abstract: A social network is a set of people or organization or other social entities connected by some form of relationships. Analysis of social network broadly elaborates visual and mathematical representation of that relationship. Web can also be considered as a social network. This paper presents an innovative approach to analyze a social network using a variant of existing ant colony optimization algorithm called as Clever Ant Colony Metaphor. Experiments are performed and interesting findings and observations have been inferred based on the proposed model.
Abstract: By taking advantage of both k-NN which is highly
accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less
subclass number, stability and bounded time of classification with respect to the variable data size. We find between 96% and 99.7 % of accuracy in the lassification of 6 different types of Time series by using K-means cluster algorithm and we find 99.7% by using the new clustering algorithm.
Abstract: Command and Control (C2) system and its interfacethe
Common Operational Picture (COP) are main means that
supports commander in its decision making process. COP contains
information about friendly and enemy unit positions. The friendly
position is gathered via tactical network. In the case of tactical
network failure the information about units are not available. The
tactical simulator can be used as a tool that is capable to predict
movements of units in respect of terrain features. Article deals with
an experiment that was based on Czech C2 system that is in the case
of connectivity lost fed by VR Forces simulator. Article analyzes
maximum time interval in which the position created by simulator is
still usable and truthful for commander in real time.
Abstract: Lossless compression schemes with secure
transmission play a key role in telemedicine applications that helps in
accurate diagnosis and research. Traditional cryptographic algorithms
for data security are not fast enough to process vast amount of data.
Hence a novel Secured lossless compression approach proposed in
this paper is based on reversible integer wavelet transform, EZW
algorithm, new modified runlength coding for character
representation and selective bit scrambling. The use of the lifting
scheme allows generating truly lossless integer-to-integer wavelet
transforms. Images are compressed/decompressed by well-known
EZW algorithm. The proposed modified runlength coding greatly
improves the compression performance and also increases the
security level. This work employs scrambling method which is fast,
simple to implement and it provides security. Lossless compression
ratios and distortion performance of this proposed method are found
to be better than other lossless techniques.
Abstract: Response surface methodology was used for
quantitative investigation of water and solids transfer during osmotic
dehydration of beetroot in aqueous solution of salt. Effects of
temperature (25 – 45oC), processing time (30–150 min), salt
concentration (5–25%, w/w) and solution to sample ratio (5:1 – 25:1)
on osmotic dehydration of beetroot were estimated. Quadratic
regression equations describing the effects of these factors on the
water loss and solids gain were developed. It was found that effects
of temperature and salt concentrations were more significant on the
water loss than the effects of processing time and solution to sample
ratio. As for solids gain processing time and salt concentration were
the most significant factors. The osmotic dehydration process was
optimized for water loss, solute gain, and weight reduction. The
optimum conditions were found to be: temperature – 35oC,
processing time – 90 min, salt concentration – 14.31% and solution
to sample ratio 8.5:1. At these optimum values, water loss, solid gain
and weight reduction were found to be 30.86 (g/100 g initial sample),
9.43 (g/100 g initial sample) and 21.43 (g/100 g initial sample)
respectively.
Abstract: For many chemical and biological processes, the understanding of the mixing phenomenon and flow behavior in a stirred tank is of major importance. A three-dimensional numerical study was performed using the software Fluent, to study the flow field in a stirred tank with a Rushton turbine. In this work, we first studied the flow generated in the tank with a Rushton turbine. Then, we studied the effect of the variation of turbine’s submergence on the thermodynamic quantities defining the flow field. For that, four submergences were considered, while maintaining the same rotational speed (N =250rpm). This work intends to optimize the aeration performances of a Rushton turbine in a stirred tank.
Abstract: Truss spars are used for oil exploitation in deep and ultra-deep water if storage crude oil is not needed. The linear hydrodynamic analysis of truss spar in random sea wave load is necessary for determining the behaviour of truss spar. This understanding is not only important for design of the mooring lines, but also for optimising the truss spar design. In this paper linear hydrodynamic analysis of truss spar is carried out in frequency domain. The hydrodynamic forces are calculated using the modified Morison equation and diffraction theory. Added mass and drag coefficients of truss section computed by transmission matrix and normal acceleration and velocity component acting on each element and for hull section computed by strip theory. The stiffness properties of the truss spar can be separated into two components; hydrostatic stiffness and mooring line stiffness. Then, platform response amplitudes obtained by solved the equation of motion. This equation is non-linear due to viscous damping term therefore linearised by iteration method [1]. Finally computed RAOs and significant response amplitude and results are compared with experimental data.
Abstract: A biophysically based multilayer continuum model of the facial soft tissue composite has been developed for simulating wrinkle formation. The deformed state of the soft tissue block was determined by solving large deformation mechanics equations using the Galerkin finite element method. The proposed soft tissue model is composed of four layers with distinct mechanical properties. These include stratum corneum, epidermal-dermal layer (living epidermis and dermis), subcutaneous tissue and the underlying muscle. All the layers were treated as non-linear, isotropic Mooney Rivlin materials. Contraction of muscle fibres was approximated using a steady-state relationship between the fibre extension ratio, intracellular calcium concentration and active stress in the fibre direction. Several variations of the model parameters (stiffness and thickness of epidermal-dermal layer, thickness of subcutaneous tissue layer) have been considered.
Abstract: Three dimensional simulations in tube in tube heat
exchangers are investigated numerically in this study. In these
simulations forced convective heat transfer and laminar flow of
single-phase water are considered. In order to measure heat transfer
parameters in these heat exchangers, FLUENT CFD Solver is used in
this numerical method. For the purpose of creating geometry and
exert boundary and initial conditions in the present model, finite
volume method in Computational Fluid Dynamics is used in this
study. In the present study, at each Z-location, variation of local
temperatures, heat flux and Nusselt number at the whole tube is
investigated in detail. Thereafter, averaged computational Nusselt
number in this model is calculated. In addition, conceivable pressure
drops have been obtained at each Z-location in this model. Then,
pressure drop values in the present model are explored. Finally, all
the numerical results for this kind of heat exchanger will be discussed
precisely.
Abstract: This paper presents a highly efficient algorithm for detecting and tracking humans and objects in video surveillance sequences. Mean shift clustering is applied on backgrounddifferenced image sequences. For efficiency, all calculations are performed on integral images. Novel corresponding exponential integral kernels are introduced to allow the application of nonuniform kernels for clustering, which dramatically increases robustness without giving up the efficiency of the integral data structures. Experimental results demonstrating the power of this approach are presented.
Abstract: Wavelets have provided the researchers with
significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional
by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to
detect the defect of texture images by using curvelet transform.
Simulation results of the proposed method on a set of standard
texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing
discontinuity in two-dimensional functions compared to wavelet
transform
Abstract: Structural and UV/Visible optical properties can be
useful to describe a material for the CIGS solar cell active layer,
therefore, this work demonstrates the properties like surface
morphology, X-ray Photoelectron Spectroscopy (XPS) bonding
energy (EB) core level spectra, UV/Visible absorption spectra,
refractive index (n), optical energy band (Eg), reflection spectra for
the Cu25 (In16Ga9) Se40Te10 (CIGST-1) and Cu20 (In14Ga9) Se45Te12
(CIGST-2) chalcogenide compositions. Materials have been
exhibited homogenous surface morphologies, broading /-or diffusion
of bonding energy peaks relative elemental values and a high
UV/Visible absorption tendency in the wave length range 400 nm-
850 nm range with the optical energy band gaps 1.37 and 1.42
respectively. Subsequently, UV/Visible reflectivity property in the
wave length range 250 nm to 320 nm for these materials has also
been discussed.
Abstract: The urban centers within northeastern Brazil are
mainly influenced by the intense rainfalls, which can occur after long
periods of drought, when flood events can be observed during such
events. Thus, this paper aims to study the rainfall frequencies in such
region through the wavelet transform. An application of wavelet
analysis is done with long time series of the total monthly rainfall
amount at the capital cities of northeastern Brazil. The main
frequency components in the time series are studied by the global
wavelet spectrum and the modulation in separated periodicity bands
were done in order to extract additional information, e.g., the 8 and
16 months band was examined by an average of all scales, giving a
measure of the average annual variance versus time, where the
periods with low or high variance could be identified. The important
increases were identified in the average variance for some periods,
e.g. 1947 to 1952 at Teresina city, which can be considered as high
wet periods. Although, the precipitation in those sites showed similar
global wavelet spectra, the wavelet spectra revealed particular
features. This study can be considered an important tool for time
series analysis, which can help the studies concerning flood control,
mainly when they are applied together with rainfall-runoff
simulations.
Abstract: There are three main ways of categorizing capital in banking operations: accounting, regulatory and economic capital. However, the 2008-2009 global crisis has shown that none of these categories adequately reflects the real risks of bank operations, especially in light of the failures Bear Stearns, Lehman Brothers or Northern Rock. This paper deals with the economic capital allocation of global banks. In theory, economic capital should reflect the real risks of a bank and should be publicly available. Yet, as discovered during the global financial crisis, even when economic capital information was publicly disclosed, the underlying assumptions rendered the information useless. Specifically, some global banks that reported relatively high levels of economic capital before the crisis went bankrupt or had to be bailed-out by their government. And, only 15 out of 50 global banks reported their economic capital during the 2007-2010 period. In this paper, we analyze the changes in reported bank economic capital disclosure during this period. We conclude that relative shares of credit and business risks increased in 2010 compared to 2007, while both operational and market risks decreased their shares on the total economic capital of top-rated global banks. Generally speaking, higher levels of disclosure and transparency of bank operations are required to obtain more confidence from stakeholders. Moreover, additional risks such as liquidity risks should be included in these disclosures.
Abstract: Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no explicit model of the data is assumed. Therefore due to the high dimensionality of the data, linearization of the training problem through use of orthogonal basis functions is not desirable. The focus is functional minimization on any basis. A number of methods based on local gradient and Hessian matrices are discussed. Modifications of many methods of first and second order training methods are considered. Using share rates data, experimentally it is proved that Conjugate gradient and Quasi Newton?s methods outperformed the Gradient Descent methods. In case of the Levenberg-Marquardt algorithm is of special interest in financial forecasting.
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: RoboCup Rescue simulation as a large-scale Multi
agent system (MAS) is one of the challenging environments for
keeping coordination between agents to achieve the objectives
despite sensing and communication limitations. The dynamicity of
the environment and intensive dependency between actions of
different kinds of agents make the problem more complex. This point
encouraged us to use learning-based methods to adapt our decision
making to different situations. Our approach is utilizing
reinforcement leaning. Using learning in rescue simulation is one of
the current ways which has been the subject of several researches in
recent years. In this paper we present an innovative learning method
implemented for Police Force (PF) Agent. This method can cope
with the main difficulties that exist in other learning approaches.
Different methods used in the literature have been examined. Their
drawbacks and possible improvements have led us to the method
proposed in this paper which is fast and accurate. The Brain
Emotional Learning Based Intelligent Controller (BELBIC) is our
solution for learning in this environment. BELBIC is a
physiologically motivated approach based on a computational model
of amygdale and limbic system. The paper presents the results
obtained by the proposed approach, showing the power of BELBIC
as a decision making tool in complex and dynamic situation.
Abstract: The analysis is mainly concentrating on the knowledge
management literatures productivity trend which subjects as
“knowledge management" in SSCI database. The purpose what the
analysis will propose is to summarize the trend information for
knowledge management researchers since core knowledge will be
concentrated in core categories. The result indicated that the literature
productivity which topic as “knowledge management" is still
increasing extremely and will demonstrate the trend by different
categories including author, country/territory, institution name,
document type, language, publication year, and subject area. Focus on
the right categories, you will catch the core research information. This
implies that the phenomenon "success breeds success" is more
common in higher quality publications.
Abstract: LabVIEW and SIMULINK are two most widely used
graphical programming environments for designing digital signal
processing and control systems. Unlike conventional text-based
programming languages such as C, Cµ and MATLAB, graphical
programming involves block-based code developments, allowing a
more efficient mechanism to build and analyze control systems. In
this paper a LabVIEW environment has been employed as a
graphical user interface for monitoring the operation of a controlled
distillation column, by visualizing both the closed loop performance
and the user selected control conditions, while the column dynamics
has been modeled under the SIMULINK environment. This tool has
been applied to the PID based decoupled control of a binary
distillation column. By means of such integrated environments the
control designer is able to monitor and control the plant behavior and
optimize the response when both, the quality improvement of
distillation products and the operation efficiency tasks, are
considered.