Abstract: This paper proposes a method that discovers time series event patterns from textual data with time information. The patterns are composed of sequences of events and each event is extracted from the textual data, where an event is characteristic content included in the textual data such as a company name, an action, and an impression of a customer. The method introduces 7 types of time constraints based on the analysis of the textual data. The method also evaluates these constraints when the frequency of a time series event pattern is calculated. We can flexibly define the time constraints for interesting combinations of events and can discover valid time series event patterns which satisfy these conditions. The paper applies the method to daily business reports collected by a sales force automation system and verifies its effectiveness through numerical experiments.
Abstract: In this paper we introduce a novel method for
the characterization of synchronziation and coupling effects
in multivariate time series that can be used for the analysis
of EEG or ECoG signals recorded during epileptic seizures.
The method allows to visualize the spatio-temporal evolution
of synchronization and coupling effects that are characteristic
for epileptic seizures. Similar to other methods proposed for
this purpose our method is based on a regression analysis.
However, a more general definition of the regression together
with an effective channel selection procedure allows to use the
method even for time series that are highly correlated, which
is commonly the case in EEG/ECoG recordings with large
numbers of electrodes. The method was experimentally tested
on ECoG recordings of epileptic seizures from patients with
temporal lobe epilepsies. A comparision with the results from
a independent visual inspection by clinical experts showed
an excellent agreement with the patterns obtained with the
proposed method.
Abstract: Recognizing behavioral patterns of financial markets
is essential for traders. Japanese candlestick chart is a common tool to
visualize and analyze such patterns in an economic time series. Since
the world was introduced to Japanese candlestick charting, traders
saw how combining this tool with intelligent technical approaches
creates a powerful formula for the savvy investors.
This paper propose a generalization to box counting method of
Grassberger-Procaccia, which is based on computing the correlation
dimension of Japanese candlesticks instead commonly used 'close'
points. The results of this method applied on several foreign
exchange rates vs. IRR (Iranian Rial). Satisfactorily show lower
chaotic dimension of Japanese candlesticks series than regular
Grassberger-Procaccia method applied merely on close points of
these same candles. This means there is some valuable information
inside candlesticks.
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 focus of this paper is to construct daily time series
exchange rate forecast models of Samoan Tala/USD and Tala/AUD
during the year 2008 to 2012 with neural network The performance
of the models was measured by using varies error functions such as
Root Square mean error (RSME), Mean absolute error (MAE), and
Mean absolute percentage error (MAPE). Our empirical findings
suggest that AR (1) model is an effective tool to forecast the
Tala/USD and Tala/AUD.
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: This paper describes Independent Component Analysis (ICA) based fixed-point algorithm for the blind separation of the convolutive mixture of speech, picked-up by a linear microphone array. The proposed algorithm extracts independent sources by non- Gaussianizing the Time-Frequency Series of Speech (TFSS) in a deflationary way. The degree of non-Gaussianization is measured by negentropy. The relative performances of algorithm under random initialization and Null beamformer (NBF) based initialization are studied. It has been found that an NBF based initial value gives speedy convergence as well as better separation performance
Abstract: In this paper, design, fabrication and coupled
multifield analysis of hollow out-of-plane silicon microneedle array
with piezoelectrically actuated microfluidic device for transdermal
drug delivery (TDD) applications is presented. The fabrication
process of silicon microneedle array is first done by series of
combined isotropic and anisotropic etching processes using
inductively coupled plasma (ICP) etching technology. Then coupled
multifield analysis of MEMS based piezoelectrically actuated device
with integrated 2×2 silicon microneedle array is presented. To predict
the stress distribution and model fluid flow in coupled field analysis,
finite element (FE) and computational fluid dynamic (CFD) analysis
using ANSYS rather than analytical systems has been performed.
Static analysis and transient CFD analysis were performed to predict
the fluid flow through the microneedle array. The inlet pressure from
10 kPa to 150 kPa was considered for static CFD analysis. In the
lumen region fluid flow rate 3.2946 μL/min is obtained at 150 V for
2×2 microneedle array. In the present study the authors have
performed simulation of structural, piezoelectric and CFD analysis
on three dimensional model of the piezoelectrically actuated
mcirofluidic device integrated with 2×2 microneedle array.
Abstract: In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Abstract: The influence of extrusion parameters on surface
quality and properties of AA6061+x% vol. SiC (x = 0; 2,5; 5; 7,5;10)
composites was discussed in this paper. The averages size of
AA6061 and SiC particles were 10.6 μm and 0.42 μm, respectively.
Two series of composites (I - compacts were preheated at extrusion
temperature through 0.5 h and cooled by water directly after process;
II - compacts were preheated through 3 hours and were not cooled)
were consolidated via powder metallurgy processing and extruded by
KoBo method. High values of density for both series of composites
were achieved. Better surface quality was observed for II series of
composites. Moreover, for these composites lower (compared to I
series) but more uniform strength properties over the cross-section of
the bar were noticed. Microstructure and Young-s modulus
investigations were made.
Abstract: Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrollments of the University of Alabama. In recent years, a number of techniques have been proposed for forecasting based on fuzzy set theory methods. These methods have either used enrollment numbers or differences of enrollments as the universe of discourse. We propose using the year to year percentage change as the universe of discourse. In this communication, the approach of Jilani, Burney, and Ardil is modified by using the year to year percentage change as the universe of discourse. We use enrollment figures for the University of Alabama to illustrate our proposed method. The proposed method results in better forecasting accuracy than existing models.
Abstract: A generalized unified power quality conditioner
(GUPQC) by using three single-phase three-level voltage source
converters (VSCs) connected back-to-back through a common dc
link is proposed in this paper as a new custom power device for a
three-feeder distribution system. One of the converters is connected
in shunt with one feeder for mitigation of current harmonics and
reactive power compensation, while the other two VSCs are
connected in series with the other two feeders to maintain the load
voltage sinusoidal and at constant level. A new control scheme based
on synchronous reference frame is proposed for series converters.
The simulation analysis on compensation performance of GUPQC
based on PSCAD/EMTDC is reported.
Abstract: Uncertainties of a serial production line affect on the
production throughput. The uncertainties cannot be prevented in a
real production line. However the uncertain conditions can be
controlled by a robust prediction model. Thus, a hybrid model
including autoregressive integrated moving average (ARIMA) and
multiple polynomial regression, is proposed to model the nonlinear
relationship of production uncertainties with throughput. The
uncertainties under consideration of this study are demand, breaktime,
scrap, and lead-time. The nonlinear relationship of production
uncertainties with throughput are examined in the form of quadratic
and cubic regression models, where the adjusted R-squared for
quadratic and cubic regressions was 98.3% and 98.2%. We optimized
the multiple quadratic regression (MQR) by considering the time
series trend of the uncertainties using ARIMA model. Finally the
hybrid model of ARIMA and MQR is formulated by better adjusted
R-squared, which is 98.9%.
Abstract: This paper discusses the performance modeling and availability analysis of Yarn Dyeing System of a Textile Industry. The Textile Industry is a complex and repairable engineering system. Yarn Dyeing System of Textile Industry consists of five subsystems arranged in series configuration. For performance modeling and analysis of availability, a performance evaluating model has been developed with the help of mathematical formulation based on Markov-Birth-Death Process. The differential equations have been developed on the basis of Probabilistic Approach using a Transition Diagram. These equations have further been solved using normalizing condition in order to develop the steady state availability, a performance measure of the system concerned. The system performance has been further analyzed with the help of decision matrices. These matrices provide various availability levels for different combinations of failure and repair rates for various subsystems. The findings of this paper are therefore, considered to be useful for the analysis of availability and determination of the best possible maintenance strategies which can be implemented in future to enhance the system performance.
Abstract: In this paper, the application of multiple Elman neural networks to time series data regression problems is studied. An ensemble of Elman networks is formed by boosting to enhance the performance of the individual networks. A modified version of the AdaBoost algorithm is employed to integrate the predictions from multiple networks. Two benchmark time series data sets, i.e., the Sunspot and Box-Jenkins gas furnace problems, are used to assess the effectiveness of the proposed system. The simulation results reveal that an ensemble of boosted Elman networks can achieve a higher degree of generalization as well as performance than that of the individual networks. The results are compared with those from other learning systems, and implications of the performance are discussed.
Abstract: The purpose of this paper is to detect human in images.
This paper proposes a method for extracting human body feature descriptors consisting of projected edge component series. The feature descriptor can express appearances and shapes of human with local
and global distribution of edges. Our method evaluated with a linear SVM classifier on Daimler-Chrysler pedestrian dataset, and test with
various sub-region size. The result shows that the accuracy level of
proposed method similar to Histogram of Oriented Gradients(HOG)
feature descriptor and feature extraction process is simple and faster than existing methods.
Abstract: Free convection effects and heat transfer due to a pulsating point heat source embedded in an infinite, fluid saturated, porous dusty medium are studied analytically. Both velocity and temperature fields are discussed in the form of series expansions in the Rayleigh number, for both the fluid and particle phases based on the mean heat generation rate from source and on the permeability of the porous dusty medium. This study is carried out by assuming the Rayleigh number small and the validity of Darcy-s law. Analytical expressions for both phases are obtained for second order mean in both velocity and temperature fields and evolution of different wave patterns are observed in the fluctuating part. It has been observed that, at the vicinity of the origin, the second order mean flow is influenced only by relaxation time of dust particles and not by dust concentration.
Abstract: Topical photodynamic therapy (PDT) with
5-aminolevulinic acid (ALA) is an alternative therapy for treating
superficial cancer, especially for skin or oral cancer. ALA, a precursor
of the photosensitizer protoporphyrin IX (PpIX), is present as
zwitterions and hydrophilic property which make the low permeability
through the cell membrane. Collagen is a traditional carrier; its
molecular composed various amino acids which bear positive charge
and negative charge. In order to utilize the ion-pairs with ALA and
collagen, the study employed various pH values adjusting the net
charge. The aim of this study was to compare a series collagen form,
including solution, gel and sponge to investigate the topical delivery
behavior of ALA. The in vivo confocal laser scanning microscopy
(CLSM) study demonstrated that PpIX generation ability was different
pattern after apply for 6 h. Gel type could generate high PpIX, and
archived more deep of skin depth.
Abstract: Methods to detect and localize time singularities of polynomial and quasi-polynomial ordinary differential equations are systematically presented and developed. They are applied to examples taken form different fields of applications and they are also compared to better known methods such as those based on the existence of linear first integrals or Lyapunov functions.
Abstract: The development of Internet technology in recent years has led to a more active role of users in creating Web content. This has significant effects both on individual learning and collaborative knowledge building. This paper will present an integrative framework model to describe and explain learning and knowledge building with shared digital artifacts on the basis of Luhmann-s systems theory and Piaget-s model of equilibration. In this model, knowledge progress is based on cognitive conflicts resulting from incongruities between an individual-s prior knowledge and the information which is contained in a digital artifact. Empirical support for the model will be provided by 1) applying it descriptively to texts from Wikipedia, 2) examining knowledge-building processes using a social network analysis, and 3) presenting a survey of a series of experimental laboratory studies.