Abstract: Computer game industry has experienced exponential
growth in recent years. A game is a recreational activity involving
one or more players. Game input is information such as data,
commands, etc., which is passed to the game system at run time from
an external source. Conversely, game outputs are information which
are generated by the game system and passed to an external target,
but which is not used internally by the game. This paper identifies a
new classification scheme for game input and output, which is based
on player-s input and output. Using this, relationship table for game
input classifier and output classifier is developed.
Abstract: Six parameters, the effective diffusivity (De),
activation energy of De, pre-exponential factor of De, amount
(ASOW) of self-organized water species, and amplitude (α) of the
forced oscillation of the molecular mobility (1/tC) derived from the
forced cyclic temperature change operation, were characterized by
using six typical foods, squid, sardines, scallops, salmon, beef, and
pork, as a function of the correlation time (tC) of the water molecule-s
proton retained in the foods. Each of the six parameters was clearly
divided into the water species A1 and A2 at a specified value of tC
=10-8s (=CtC), indicating an anomalous change in the physicochemical
nature of the water species at the CtC. The forced oscillation of 1/tC
clearly demonstrated a characteristic mode depending on the food
shown as a three dimensional map associated with 1/tC, the amount of
self-organized water, and tC.
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: The purpose of this study is comparing and analysing
of the financial characteristics for development methods of the urban development project in the established area, focusing on the
multi-level replotting.
Analysis showed that the type of the lowest expenditure was
'combination type of group-land and multi-level replotting' and the type of the highest profitability was 'multi-level replotting type'. But
'multi-level replotting type' has still risk of amount of cost for the additional architecture. In addition, we subdivided standard amount
for liquidation of replotting and analysed income-expenditure flow.
Analysis showed that both of 'multi-level replotting type' and 'combination type of group-land and multi-level replotting' improved
profitability of project and property change ratio. However, when the
standard was under a certain amount, amount of original property for the replotting was increased exponentially, and profitability of project.
Abstract: In the present communication, the existing measures of
fuzzy entropy are reviewed. A generalized parametric exponential
fuzzy entropy is defined.Our study of the four essential and some
other properties of the proposed measure, clearly establishes the
validity of the measure as an entropy.
Abstract: In the recent years, high dynamic range imaging has
gain popularity with the advancement in digital photography. In this
contribution we present a subjective evaluation of various tone
production and tone mapping techniques by a number of participants.
Firstly, standard HDR images were used and the participants were
asked to rate them based on a given rating scheme. After that, the
participant was asked to rate HDR image generated using linear and
nonlinear combination approach of multiple exposure images. The
experimental results showed that linearly generated HDR images
have better visualization than the nonlinear combined ones. In
addition, Reinhard et al. and the exponential tone mapping operators
have shown better results compared to logarithmic and the Garrett et
al. tone mapping operators.
Abstract: A Variable Structure Model Reference Adaptive Controller using state variables is proposed for a class of multi input-multi output systems. Adaptation law is of variable structure type and switching functions is designed based on stability requirements. Global exponential stability is proved based on Lyapunov criterion. Transient behavior is analyzed using sliding mode control and shows perfect model following at a finite time.
Abstract: This paper reports a new and accurate method for load-flow solution of radial distribution networks with minimum data preparation. The node and branch numbering need not to be sequential like other available methods. The proposed method does not need sending-node, receiving-node and branch numbers if these are sequential. The proposed method uses the simple equation to compute the voltage magnitude and has the capability to handle composite load modelling. The proposed method uses the set of nodes of feeder, lateral(s) and sub lateral(s). The effectiveness of the proposed method is compared with other methods using two examples. The detailed load-flow results for different kind of load-modellings are also presented.
Abstract: The double exponential model (DEM), or Laplace
distribution, is used in various disciplines. However, there are issues
related to the construction of confidence intervals (CI), when using
the distribution.In this paper, the properties of DEM are considered
with intention of constructing CI based on simulated data. The
analysis of pivotal equations for the models here in comparisons with
pivotal equations for normal distribution are performed, and the
results obtained from simulation data are presented.
Abstract: Spare parts inventory management is one of the major
areas of inventory research. Analysis of recent literature showed that
an approach integrating spare parts classification, demand
forecasting, and stock control policies is essential; however, adapting
this integrated approach is limited. This work presents an integrated
framework for spare part inventory management and an Excel based
application developed for the implementation of the proposed
framework. A multi-criteria analysis has been used for spare
classification. Forecasting of spare parts- intermittent demand has
been incorporated into the application using three different
forecasting models; namely, normal distribution, exponential
smoothing, and Croston method. The application is also capable of
running with different inventory control policies. To illustrate the
performance of the proposed framework and the developed
application; the framework is applied to different items at a service
organization. The results achieved are presented and possible areas
for future work are highlighted.
Abstract: In this paper we use exponential particle swarm
optimization (EPSO) to cluster data. Then we compare between
(EPSO) clustering algorithm which depends on exponential variation
for the inertia weight and particle swarm optimization (PSO)
clustering algorithm which depends on linear inertia weight. This
comparison is evaluated on five data sets. The experimental results
show that EPSO clustering algorithm increases the possibility to find
the optimal positions as it decrease the number of failure. Also show
that (EPSO) clustering algorithm has a smaller quantization error
than (PSO) clustering algorithm, i.e. (EPSO) clustering algorithm
more accurate than (PSO) clustering algorithm.
Abstract: In this paper, we investigate the appearance of the giant component in random subgraphs G(p) of a given large finite graph family Gn = (Vn, En) in which each edge is present independently with probability p. We show that if the graph Gn satisfies a weak isoperimetric inequality and has bounded degree, then the probability p under which G(p) has a giant component of linear order with some constant probability is bounded away from zero and one. In addition, we prove the probability of abnormally large order of the giant component decays exponentially. When a contact graph is modeled as Gn, our result is of special interest in the study of the spread of infectious diseases or the identification of community in various social networks.
Abstract: In the queueing theory, it is assumed that customer
arrivals correspond to a Poisson process and service time has the
exponential distribution. Using these assumptions, the behaviour of
the queueing system can be described by means of Markov chains
and it is possible to derive the characteristics of the system. In the
paper, these theoretical approaches are presented on several types of
systems and it is also shown how to compute the characteristics in a
situation when these assumptions are not satisfied
Abstract: In the present communication, stochastic comparison
of a series (parallel) system having heterogeneous components with
random lifetimes and series (parallel) system having homogeneous
exponential components with random lifetimes has been studied.
Further, conditions under which such a comparison is possible has
been established.
Abstract: The use of buffer thresholds, blocking and adequate
service strategies are well-known techniques for computer networks
traffic congestion control. This motivates the study of series queues
with blocking, feedback (service under Head of Line (HoL) priority
discipline) and finite capacity buffers with thresholds. In this paper,
the external traffic is modelled using the Poisson process and the
service times have been modelled using the exponential distribution.
We consider a three-station network with two finite buffers, for
which a set of thresholds (tm1 and tm2) is defined. This computer
network behaves as follows. A task, which finishes its service at
station B, gets sent back to station A for re-processing with
probability o. When the number of tasks in the second buffer exceeds
a threshold tm2 and the number of task in the first buffer is less than
tm1, the fed back task is served under HoL priority discipline. In
opposite case, for fed backed tasks, “no two priority services in
succession" procedure (preventing a possible overflow in the first
buffer) is applied. Using an open Markovian queuing schema with
blocking, priority feedback service and thresholds, a closed form
cost-effective analytical solution is obtained. The model of servers
linked in series is very accurate. It is derived directly from a twodimensional
state graph and a set of steady-state equations, followed
by calculations of main measures of effectiveness. Consequently,
efficient expressions of the low computational cost are determined.
Based on numerical experiments and collected results we conclude
that the proposed model with blocking, feedback and thresholds can
provide accurate performance estimates of linked in series networks.
Abstract: Eigenvector methods are gaining increasing acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
Abstract: This paper presents a new fingerprint coding technique
based on contourlet transform and multistage vector quantization.
Wavelets have shown their ability in representing natural images that
contain smooth areas separated with edges. However, wavelets
cannot efficiently take advantage of the fact that the edges usually
found in fingerprints are smooth curves. This issue is addressed by
directional transforms, known as contourlets, which have the
property of preserving edges. The contourlet transform is a new
extension to the wavelet transform in two dimensions using
nonseparable and directional filter banks. The computation and
storage requirements are the major difficulty in implementing a
vector quantizer. In the full-search algorithm, the computation and
storage complexity is an exponential function of the number of bits
used in quantizing each frame of spectral information. The storage
requirement in multistage vector quantization is less when compared
to full search vector quantization. The coefficients of contourlet
transform are quantized by multistage vector quantization. The
quantized coefficients are encoded by Huffman coding. The results
obtained are tabulated and compared with the existing wavelet based
ones.
Abstract: Saddlepoint approximations is one of the tools to obtain
an expressions for densities and distribution functions. We approximate
the densities of the observed gaps between the hypopnea events
using the Huzurbazar saddlepoint approximation. We demonstrate the
density of a maximum likelihood estimator in exponential families.
Abstract: In this paper, the discrete-time fuzzy BAM neural network with delays and impulses is studied. Sufficient conditions are obtained for the existence and global stability of a unique equilibrium of this class of fuzzy BAM neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Some numerical examples are given to demonstrate the effectiveness of the obtained results.
Abstract: How to coordinate the behaviors of the agents through
learning is a challenging problem within multi-agent domains.
Because of its complexity, recent work has focused on how
coordinated strategies can be learned. Here we are interested in using
reinforcement learning techniques to learn the coordinated actions of a
group of agents, without requiring explicit communication among
them. However, traditional reinforcement learning methods are based
on the assumption that the environment can be modeled as Markov
Decision Process, which usually cannot be satisfied when multiple
agents coexist in the same environment. Moreover, to effectively
coordinate each agent-s behavior so as to achieve the goal, it-s
necessary to augment the state of each agent with the information
about other existing agents. Whereas, as the number of agents in a
multiagent environment increases, the state space of each agent grows
exponentially, which will cause the combinational explosion problem.
Profit sharing is one of the reinforcement learning methods that allow
agents to learn effective behaviors from their experiences even within
non-Markovian environments. In this paper, to remedy the drawback
of the original profit sharing approach that needs much memory to
store each state-action pair during the learning process, we firstly
address a kind of on-line rational profit sharing algorithm. Then, we
integrate the advantages of modular learning architecture with on-line
rational profit sharing algorithm, and propose a new modular
reinforcement learning model. The effectiveness of the technique is
demonstrated using the pursuit problem.