Abstract: Cyber physical system (CPS) for target tracking, military surveillance, human health monitoring, and vehicle detection all require maximizing the utility and saving the energy. Sensor selection is one of the most important parts of CPS. Sensor selection problem (SSP) is concentrating to balance the tradeoff between the number of sensors which we used and the utility which we will get. In this paper, we propose a performance constrained slide windows (PCSW) based algorithm for SSP in CPS. we present results of extensive simulations that we have carried out to test and validate the PCSW algorithms when we track a target, Experiment shows that the PCSW based algorithm improved the performance including selecting time and communication times for selecting.
Abstract: Global warming and continental changes have been
one of the people's issues in the recent years and its consequences
have appeared in the most parts of the earth planet or will appear in
the future. Temperature and Precipitation are two main parameters in
climatology. Any changes in these two parameters in this region
cause widespread changes in the ecosystem and its natural and
humanistic structure. One of the important consequences of this
procedure is change in surface and underground water resources.
Zayanderood watershed basin which is the main central river in Iran
has faced water shortage in the recent years and also it has resulted in
drought in Gavkhuni swamp and the river itself. Managers and
experts in provinces which are the Zayanderood water consumers
believe that global warming; raining decrease and continental
changes are the main reason of water decrease. By statistical
investigation of annual Precipitation and 46 years temperature of
internal and external areas of Zayanderood watershed basin's stations
and by using Kendal-man method, Precipitation and temperature
procedure changes have been analyzed in this basin. According to
obtained results, there was not any noticeable decrease or increase
procedure in Precipitation and annual temperature in the basin during
this period. However, regarding to Precipitation, a noticeable
decrease and increase have been observed in small part of western
and some parts of eastern and southern basin, respectively.
Furthermore, the investigation of annual temperature procedure has
shown that a noticeable increase has been observed in some parts of
western and eastern basin, and also a noticeable increasing procedure
of temperature in the central parts of metropolitan Esfahan can be
observed.
Abstract: Experimental data from an atmospheric air/water terrain slugging case has been made available by the Shell Amsterdam research center, and has been subject to numerical simulation and comparison with a one-dimensional two-phase slug tracking simulator under development at the Norwegian University of Science and Technology. The code is based on tracking of liquid slugs in pipelines by use of a Lagrangian grid formulation implemented in Cµ by use of object oriented techniques. An existing hybrid spatial discretization scheme is tested, in which the stratified regions are modelled by the two-fluid model. The slug regions are treated incompressible, thus requiring a single momentum balance over the whole slug. Upon comparison with the experimental data, the period of the simulated severe slugging cycle is observed to be sensitive to slug generation in the horizontal parts of the system. Two different slug initiation methods have been tested with the slug tracking code, and grid dependency has been investigated.
Abstract: In this paper, the implementation of a rule-based
intuitive reasoner is presented. The implementation included two
parts: the rule induction module and the intuitive reasoner. A large
weather database was acquired as the data source. Twelve weather
variables from those data were chosen as the “target variables"
whose values were predicted by the intuitive reasoner. A “complex"
situation was simulated by making only subsets of the data available
to the rule induction module. As a result, the rules induced were
based on incomplete information with variable levels of certainty.
The certainty level was modeled by a metric called "Strength of
Belief", which was assigned to each rule or datum as ancillary
information about the confidence in its accuracy. Two techniques
were employed to induce rules from the data subsets: decision tree
and multi-polynomial regression, respectively for the discrete and the
continuous type of target variables. The intuitive reasoner was tested
for its ability to use the induced rules to predict the classes of the
discrete target variables and the values of the continuous target
variables. The intuitive reasoner implemented two types of
reasoning: fast and broad where, by analogy to human thought, the
former corresponds to fast decision making and the latter to deeper
contemplation. . For reference, a weather data analysis approach
which had been applied on similar tasks was adopted to analyze the
complete database and create predictive models for the same 12
target variables. The values predicted by the intuitive reasoner and
the reference approach were compared with actual data. The intuitive
reasoner reached near-100% accuracy for two continuous target
variables. For the discrete target variables, the intuitive reasoner
predicted at least 70% as accurately as the reference reasoner. Since
the intuitive reasoner operated on rules derived from only about 10%
of the total data, it demonstrated the potential advantages in dealing
with sparse data sets as compared with conventional methods.
Abstract: This research investigates the use of digital technology
namely interactive multimedia in effective art education provided by
museum. Several multimedia experience examples created for art
education are study case subjected to assistance audiences- learning
within the context of existing theory in the field of interactive
multimedia.
Abstract: Based on assumptions of neo-classical economics and
rational choice / public choice theory, this paper investigates the
regulation of industrial land use in Taiwan by homeowners
associations (HOAs) as opposed to traditional government
administration. The comparison, which applies the transaction cost
theory and a polynomial regression analysis, manifested that HOAs
are superior to conventional government administration in terms of
transaction costs and overall efficiency. A case study that compares
Taiwan-s commonhold industrial park, NangKang Software Park, to
traditional government counterparts using limited data on the costs
and returns was analyzed. This empirical study on the relative
efficiency of governmental and private institutions justified the
important theoretical proposition. Numerical results prove the
efficiency of the established model.
Abstract: The symmetric solution set Σ sym is the set of all solutions to the linear systems Ax = b, where A is symmetric and lies between some given bounds A and A, and b lies between b and b. We present a contractor for Σ sym, which is an iterative method that starts with some initial enclosure of Σ sym (by means of a cartesian product of intervals) and sequentially makes the enclosure tighter. Our contractor is based on polyhedral approximation and solving a series of linear programs. Even though it does not converge to the optimal bounds in general, it may significantly reduce the overestimation. The efficiency is discussed by a number of numerical experiments.
Abstract: Crucial information barely visible to the human eye is
often embedded in a series of low resolution images taken of the
same scene. Super resolution reconstruction is the process of
combining several low resolution images into a single higher
resolution image. The ideal algorithm should be fast, and should add
sharpness and details, both at edges and in regions without adding
artifacts. In this paper we propose a super resolution blind
reconstruction technique for linearly degraded images. In our
proposed technique the algorithm is divided into three parts an image
registration, wavelets based fusion and an image restoration. In this
paper three low resolution images are considered which may sub
pixels shifted, rotated, blurred or noisy, the sub pixel shifted images
are registered using affine transformation model; A wavelet based
fusion is performed and the noise is removed using soft thresolding.
Our proposed technique reduces blocking artifacts and also
smoothens the edges and it is also able to restore high frequency
details in an image. Our technique is efficient and computationally
fast having clear perspective of real time implementation.
Abstract: This study was investigated on sampling and
analyzing water quality in water reservoir & water tower installed in
two kind of residential buildings and school facilities. Data of water
quality was collected for correlation analysis with frequency of
sanitization of water reservoir through questioning managers of
building about the inspection charts recorded on equipment for water
reservoir. Statistical software packages (SPSS) were applied to the
data of two groups (cleaning frequency and water quality) for
regression analysis to determine the optimal cleaning frequency of
sanitization. The correlation coefficient (R) in this paper represented
the degree of correlation, with values of R ranging from +1 to -1.After
investigating three categories of drinking water users; this study found
that the frequency of sanitization of water reservoir significantly
influenced the water quality of drinking water. A higher frequency of
sanitization (more than four times per 1 year) implied a higher quality
of drinking water. Results indicated that sanitizing water reservoir &
water tower should at least twice annually for achieving the aim of
safety of drinking water.
Abstract: This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.
Abstract: In the automotive industry test drives are being conducted
during the development of new vehicle models or as a part of
quality assurance of series-production vehicles. The communication
on the in-vehicle network, data from external sensors, or internal
data from the electronic control units is recorded by automotive
data loggers during the test drives. The recordings are used for fault
analysis. Since the resulting data volume is tremendous, manually
analysing each recording in great detail is not feasible.
This paper proposes to use machine learning to support domainexperts
by preventing them from contemplating irrelevant data and
rather pointing them to the relevant parts in the recordings. The
underlying idea is to learn the normal behaviour from available
recordings, i.e. a training set, and then to autonomously detect
unexpected deviations and report them as anomalies.
The one-class support vector machine “support vector data description”
is utilised to calculate distances of feature vectors. SVDDSUBSEQ
is proposed as a novel approach, allowing to classify subsequences
in multivariate time series data. The approach allows to
detect unexpected faults without modelling effort as is shown with
experimental results on recordings from test drives.
Abstract: The trends of design and development of information systems have undergone a variety of ongoing phases and stages. These variations have been evolved due to brisk changes in user requirements and business needs. To meet these requirements and needs, a flexible and agile business solution was required to come up with the latest business trends and styles. Another obstacle in agility of information systems was typically different treatment of same diseases of two patients: business processes and information services. After the emergence of information technology, the business processes and information systems have become counterparts. But these two business halves have been treated under totally different standards. There is need to streamline the boundaries of these both pillars that are equally sharing information system's burdens and liabilities. In last decade, the object orientation has evolved into one of the major solutions for modern business needs and now, SOA is the solution to shift business on ranks of electronic platform. BPM is another modern business solution that assists to regularize optimization of business processes. This paper discusses how object orientation can be conformed to incorporate or embed SOA in BPM for improved information systems.
Abstract: Results of Chilean wine classification based on the
information provided by an electronic nose are reported in this paper.
The classification scheme consists of two parts; in the first stage,
Principal Component Analysis is used as feature extraction method to
reduce the dimensionality of the original information. Then, Radial
Basis Functions Neural Networks is used as pattern recognition
technique to perform the classification. The objective of this study is
to classify different Cabernet Sauvignon, Merlot and Carménère wine
samples from different years, valleys and vineyards of Chile.
Abstract: Previous the 3D model texture generation from multi-view images and mapping algorithms has issues in the texture chart generation which are the self-intersection and the concentration of the texture in texture space. Also we may suffer from some problems due to the occluded areas, such as inside parts of thighs. In this paper we propose a texture mapping technique for 3D models using multi-view images on the GPU. We do texture mapping directly on the GPU fragment shader per pixel without generation of the texture map. And we solve for the occluded area using the 3D model depth information. Our method needs more calculation on the GPU than previous works, but it has shown real-time performance and previously mentioned problems do not occur.
Abstract: The present study was designed to investigate the
cardio protective role of chronic oral administration of alcoholic
extract of Terminalia arjuna in in-vivo ischemic reperfusion injury
and the induction of HSP72. Rabbits, divided into three groups, and
were administered with the alcoholic extract of the bark powder of
Terminalia arjuna (TAAE) by oral gavage [6.75mg/kg: (T1) and
9.75mg/kg: (T2), 6 days /week for 12 weeks]. In open-chest
Ketamine pentobarbitone anaesthetized rabbits, the left anterior
descending coronary artery was occluded for 15 min of ischemia
followed by 60 min of reperfusion. In the vehicle-treated group,
ischemic-reperfusion injury (IRI) was evidenced by depression of
global hemodynamic function (MAP, HR, LVEDP, peak LV (+) & (-
) (dP/dt) along with depletion of HEP compounds. Oxidative stress
in IRI was evidenced by, raised levels of myocardial TBARS and
depletion of endogenous myocardial antioxidants GSH, SOD and
catalase. Western blot analysis showed a single band corresponding
to 72 kDa in homogenates of hearts from rabbits treated with both the
doses. In the alcoholic extract of the bark powder of Terminalia
arjuna treatment groups, both the doses had better recovery of
myocardial hemodynamic function, with significant reduction in
TBARS, and rise in SOD, GSH, catalase were observed. The results
of the present study suggest that the alcoholic extract of the bark
powder of Terminalia arjuna in rabbit induces myocardial HSP 72
and augments myocardial endogenous antioxidants, without causing
any cellular injury and offered better cardioprotection against
oxidative stress associated with myocardial IR injury.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: The use of hard and brittle material has become
increasingly more extensive in recent years. Therefore processing of
these materials for the parts fabrication has become a challenging
problem. However, it is time-consuming to machine the hard brittle
materials with the traditional metal-cutting technique that uses
abrasive wheels. In addition, the tool would suffer excessive wear as
well. However, if ultrasonic energy is applied to the machining
process and coupled with the use of hard abrasive grits, hard and
brittle materials can be effectively machined. Ultrasonic machining
process is mostly used for the brittle materials. The present research
work has developed models using finite element approach to predict
the mechanical stresses sand strains produced in the tool during
ultrasonic machining process. Also the flow behavior of abrasive
slurry coming out of the nozzle has been studied for simulation using
ANSYS CFX module. The different abrasives of different grit sizes
have been used for the experimentation work.
Abstract: Metal stamping die design is a complex, experiencebased
and time-consuming task. Various artificial intelligence (AI)
techniques are being used by worldwide researchers for stamping die
design to reduce complexity, dependence on human expertise and
time taken in design process as well as to improve design efficiency.
In this paper a comprehensive review of applications of AI
techniques in manufacturability evaluation of sheet metal parts, die
design and process planning of metal stamping die is presented.
Further the salient features of major research work published in the
area of metal stamping are presented in tabular form and scope of
future research work is identified.
Abstract: Electrical Discharge Machine (EDM) is especially
used for the manufacturing of 3-D complex geometry and hard
material parts that are extremely difficult-to-machine by conventional
machining processes. In this paper authors review the research work
carried out in the development of die-sinking EDM within the past
decades for the improvement of machining characteristics such as
Material Removal Rate, Surface Roughness and Tool Wear Ratio. In
this review various techniques reported by EDM researchers for
improving the machining characteristics have been categorized as
process parameters optimization, multi spark technique, powder
mixed EDM, servo control system and pulse discriminating. At the
end, flexible machine controller is suggested for Die Sinking EDM to
enhance the machining characteristics and to achieve high-level
automation. Thus, die sinking EDM can be integrated with Computer
Integrated Manufacturing environment as a need of agile
manufacturing systems.
Abstract: The incidence of mechanical fracture of an
automobile piston rings prompted development of fracture analysis
method on this case. The three rings (two compression rings and one
oil ring) were smashed into several parts during the power-test (after
manufacturing the engine) causing piston and liner to be damaged.
The radial and oblique cracking happened on the failed piston rings.
The aim of the fracture mechanics simulations presented in this paper
was the calculation of particular effective fracture mechanics
parameters, such as J-integrals and stress intensity factors. Crack
propagation angles were calculated as well. Two-dimensional
fracture analysis of the first compression ring has been developed in
this paper using ABAQUS CAE6.5-1 software. Moreover, SEM
fractography was developed on fracture surfaces and is discussed in
this paper. Results of numerical calculations constitute the basis for
further research on real object.