Abstract: In this paper, an estimation accuracy of multiple moving
talker tracking using a microphone array is improved. The tracking
can be achieved by the adaptive method in which two algorithms are integrated, namely, the PAST (Projection Approximation Subspace
Tracking) algorithm and the IPLS (Interior Point Least Square) algorithm. When either talker begins to speak again after a silent
period, an appropriate feasible region for an evaluation function of
the IPLS algorithm might not be set. Then, the tracking fails due to the incorrect updating. Therefore, if an increment of the number of
active talkers is detected, the feasible region must be reset. Then, a low cost realization is required for the high speed tracking and a high
accuracy realization is desired for the precise tracking. In this paper,
the directions roughly estimated using the delayed-sum-array method
are used for the resetting. Several results of experiments performed in
an actual room environment show the effectiveness of the proposed method.
Abstract: Historical monuments as architectural heritage are,
economically and culturally, considered one of the key aspects for
modern communities. Cultural heritage represents a country-s
national identity and pride and maintains and enriches that country-s
culture. Therefore, conservation of the monuments remained from
our ancestors requires everybody-s serious and unremitting effort.
Conservation, renewal, restoration, and technical study of cultural
and historical matters are issues which have a special status among
various forms of art and science in the present century and this is due
to two reasons: firstly, progress of humankind in this century has
created a factor called environmental pollution which not only has
caused new destructive processes of cultural/historical monuments
but also has accelerated the previous destructive processes by several
times, and secondly, the rapid advance of various sciences, especially
chemistry, has lead to the contribution of new methods and materials
to this significant issue.
Abstract: This paper deals optimized model to investigate the
effects of peak current, pulse on time and pulse off time in EDM performance on material removal rate of titanium alloy utilizing copper tungsten as electrode and positive polarity of the electrode. The experiments are carried out on Ti6Al4V. Experiments were
conducted by varying the peak current, pulse on time and pulse off time. A mathematical model is developed to correlate the influences of these variables and material removal rate of workpiece. Design of
experiments (DOE) method and response surface methodology
(RSM) techniques are implemented. The validity test of the fit and adequacy of the proposed models has been carried out through
analysis of variance (ANOVA). The obtained results evidence that as
the material removal rate increases as peak current and pulse on time
increases. The effect of pulse off time on MRR changes with peak ampere. The optimum machining conditions in favor of material removal rate are verified and compared. The optimum machining
conditions in favor of material removal rate are estimated and verified with proposed optimized results. It is observed that the developed model is within the limits of the agreeable error (about
4%) when compared to experimental results. This result leads to desirable material removal rate and economical industrial machining to optimize the input parameters.
Abstract: Since the one-to-one word translator does not have the
facility to translate pragmatic aspects of Javanese, the parallel text
alignment model described uses a phrase pair combination. The
algorithm aligns the parallel text automatically from the beginning to
the end of each sentence. Even though the results of the phrase pair
combination outperform the previous algorithm, it is still inefficient.
Recording all possible combinations consume more space in the
database and time consuming. The original algorithm is modified by
applying the edit distance coefficient to improve the data-storage
efficiency. As a result, the data-storage consumption is 90% reduced
as well as its learning period (42s).
Abstract: Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.
Abstract: Complex networks have been intensively studied across
many fields, especially in Internet technology, biological engineering,
and nonlinear science. Software is built up out of many interacting
components at various levels of granularity, such as functions, classes,
and packages, representing another important class of complex networks.
It can also be studied using complex network theory. Over the
last decade, many papers on the interdisciplinary research between
software engineering and complex networks have been published.
It provides a different dimension to our understanding of software
and also is very useful for the design and development of software
systems. This paper will explore how to use the complex network
theory to analyze software structure, and briefly review the main
advances in corresponding aspects.
Abstract: Existing literature ondesign reasoning seems to give
either one sided accounts on expert design behaviour based on
internal processing. In the same way ecological theoriesseem to
focus one sidedly on external elementsthat result in a lack of unifying
design cognition theory. Although current extended design cognition
studies acknowledge the intellectual interaction between internal and
external resources, there still seems to be insufficient understanding
of the complexities involved in such interactive processes. As
such,this paper proposes a novelmulti-directional model for design
researchers tomap the complex and dynamic conduct controlling
behaviour in which both the computational and ecological
perspectives are integrated in a vertical manner. A clear distinction
between identified intentional and emerging physical drivers, and
relationships between them during the early phases of experts- design
process, is demonstrated by presenting a case study in which the
model was employed.
Abstract: This paper looks into detailed investigation of
thermal-hydraulic characteristics of the flow field in a fuel rod
model, especially near the spacer. The area investigate represents a
source of information on the velocity flow field, vortex, and on the
amount of heat transfer into the coolant all of which are critical for
the design and improvement of the fuel rod in nuclear power plants.
The flow field investigation uses three-dimensional Computational
Fluid Dynamics (CFD) with the Reynolds stresses turbulence model
(RSM). The fuel rod model incorporates a vertical annular channel
where three different shapes of spacers are used; each spacer shape is
addressed individually. These spacers are mutually compared in
consideration of heat transfer capabilities between the coolant and
the fuel rod model. The results are complemented with the calculated
heat transfer coefficient in the location of the spacer and along the
stainless-steel pipe.
Abstract: The RR interval series is non-stationary and unevenly
spaced in time. For estimating its power spectral density (PSD) using
traditional techniques like FFT, require resampling at uniform
intervals. The researchers have used different interpolation
techniques as resampling methods. All these resampling methods
introduce the low pass filtering effect in the power spectrum. The
lomb transform is a means of obtaining PSD estimates directly from
irregularly sampled RR interval series, thus avoiding resampling. In
this work, the superiority of Lomb transform method has been
established over FFT based approach, after applying linear and
cubicspline interpolation as resampling methods, in terms of
reproduction of exact frequency locations as well as the relative
magnitudes of each spectral component.
Abstract: The recycling of concrete, bricks and masonry rubble
as concrete aggregates is an important way to contribute to a
sustainable material flow. However, there are still various
uncertainties limiting the widespread use of Recycled Concrete
Aggregates (RCA). The fluctuations in the composition of grade
recycled aggregates and their influence on the properties of fresh and
hardened concrete are of particular concern regarding the use of
RCA. Most of problems occurring while using recycled concrete
aggregates as aggregates are due to higher porosity and hence higher
water absorption, lower mechanical strengths, residual impurities on
the surface of the RCA forming weaker bond between cement paste
and aggregate. So, the reuse of RCA is still limited. Efficient
polymer based treatment is proposed in order to reuse RCA easier.
The silicon-based polymer treatments of RCA were carried out and
were compared. This kind of treatment can improve the properties of
RCA such as the rate of water absorption on treated RCA is
significantly reduced.
Abstract: This document details the process of developing a
wireless device that captures the basic movements of the foot (plantar
flexion, dorsal flexion, abduction, adduction.), and the knee
movement (flexion). It implements a motion capture system by using
a hardware based on optical fiber sensors, due to the advantages in
terms of scope, noise immunity and speed of data transmission and
reception. The operating principle used by this system is the detection
and transmission of joint movement by mechanical elements and
their respective measurement by optical ones (in this case infrared).
Likewise, Visual Basic software is used for reception, analysis and
signal processing of data acquired by the device, generating a 3D
graphical representation in real time of each movement. The result is
a boot in charge of capturing the movement, a transmission module
(Implementing Xbee Technology) and a receiver module for
receiving information and sending it to the PC for their respective
processing.
The main idea with this device is to help on topics such as
bioengineering and medicine, by helping to improve the quality of
life and movement analysis.
Abstract: It is known that the heart interacts with and adapts to
its venous and arterial loading conditions. Various experimental
studies and modeling approaches have been developed to investigate
the underlying mechanisms. This paper presents a model of the left
ventricle derived based on nonlinear stress-length myocardial
characteristics integrated over truncated ellipsoidal geometry, and
second-order dynamic mechanism for the excitation-contraction
coupling system. The results of the model presented here describe the
effects of the viscoelastic damping element of the electromechanical
coupling system on the hemodynamic response. Different heart rates
are considered to study the pacing effects on the performance of the
left-ventricle against constant preload and afterload conditions under
various damping conditions. The results indicate that the pacing
process of the left ventricle has to take into account, among other
things, the viscoelastic damping conditions of the myofilament
excitation-contraction process.
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: This paper presents reliability evaluation techniques
which are applied in distribution system planning studies and
operation. Reliability of distribution systems is an important issue in
power engineering for both utilities and customers. Reliability is a
key issue in the design and operation of electric power distribution
systems and load. Reliability evaluation of distribution systems has
been the subject of many recent papers and the modeling and
evaluation techniques have improved considerably.
Abstract: In quality control of freeze-dried durian, crispiness is
a key quality index of the product. Generally, crispy testing has to be
done by a destructive method. A nondestructive testing of the
crispiness is required because the samples can be reused for other
kinds of testing. This paper proposed a crispiness classification
method of freeze-dried durians using fuzzy logic for decision
making. The physical changes of a freeze-dried durian include the
pores appearing in the images. Three physical features including (1)
the diameters of pores, (2) the ratio of the pore area and the
remaining area, and (3) the distribution of the pores are considered to
contribute to the crispiness. The fuzzy logic is applied for making the
decision. The experimental results comparing with food expert
opinion showed that the accuracy of the proposed classification
method is 83.33 percent.
Abstract: Data mining is the process of sifting through large
volumes of data, analyzing data from different perspectives and
summarizing it into useful information. One of the widely used
desktop applications for data mining is the Weka tool which is
nothing but a collection of machine learning algorithms implemented
in Java and open sourced under the General Public License (GPL). A
web service is a software system designed to support interoperable
machine to machine interaction over a network using SOAP
messages. Unlike a desktop application, a web service is easy to
upgrade, deliver and access and does not occupy any memory on the
system. Keeping in mind the advantages of a web service over a
desktop application, in this paper we are demonstrating how this Java
based desktop data mining application can be implemented as a web
service to support data mining across the internet.
Abstract: Project managers are the ultimate responsible for the
overall characteristics of a project, i.e. they should deliver the project
on time with minimum cost and with maximum quality. It is vital for
any manager to decide a trade-off between these conflicting
objectives and they will be benefited of any scientific decision
support tool. Our work will try to determine optimal solutions (rather
than a single optimal solution) from which the project manager will
select his desirable choice to run the project. In this paper, the
problem in project scheduling notated as
(1,T|cpm,disc,mu|curve:quality,time,cost) will be studied. The
problem is multi-objective and the purpose is finding the Pareto
optimal front of time, cost and quality of a project
(curve:quality,time,cost), whose activities belong to a start to finish
activity relationship network (cpm) and they can be done in different
possible modes (mu) which are non-continuous or discrete (disc), and
each mode has a different cost, time and quality . The project is
constrained to a non-renewable resource i.e. money (1,T). Because
the problem is NP-Hard, to solve the problem, a meta-heuristic is
developed based on a version of genetic algorithm specially adapted
to solve multi-objective problems namely FastPGA. A sample project
with 30 activities is generated and then solved by the proposed
method.
Abstract: This paper aims to develop an algorithm of finite
capacity material requirement planning (FCMRP) system for a multistage
assembly flow shop. The developed FCMRP system has two
main stages. The first stage is to allocate operations to the first and
second priority work centers and also determine the sequence of the
operations on each work center. The second stage is to determine the
optimal start time of each operation by using a linear programming
model. Real data from a factory is used to analyze and evaluate the
effectiveness of the proposed FCMRP system and also to guarantee a
practical solution to the user. There are five performance measures,
namely, the total tardiness, the number of tardy orders, the total
earliness, the number of early orders, and the average flow-time. The
proposed FCMRP system offers an adjustable solution which is a
compromised solution among the conflicting performance measures.
The user can adjust the weight of each performance measure to
obtain the desired performance. The result shows that the combination
of FCMRP NP3 and EDD outperforms other combinations
in term of overall performance index. The calculation time for the
proposed FCMRP system is about 10 minutes which is practical for
the planners of the factory.
Abstract: In this paper, a Biochemical Methane Potential (BMP)
test provides a measure of the energy production potential from codigestion
between the frozen seafood wastewater and the decanter
cake. The experiments were conducted in laboratory-scale. The
suitable ratio of the frozen seafood wastewater and the decanter cake
was observed in the BMP test. The ratio of the co-digestion between
the frozen seafood wastewater and the decanter cake has impacts on
the biogas production and energy production potential. The best
performance for energy production potential using BMP test
observed from the 180 ml of the frozen seafood wastewater and 10 g
of the decanter cake ratio. This ratio provided the maximum methane
production at 0.351 l CH4/g TCODremoval. The removal efficiencies
are 76.18%, 83.55%, 43.16% and 56.76% at TCOD, SCOD, TS and
VS, respectively. The result can be concluded that the decanter cake
can improve the energy production potential of the frozen seafood
wastewater. The energy provides from co-digestion between frozen
seafood wastewater and decanter cake approximately 19x109
MJ/year in Thailand.
Abstract: One important objective in Precision Agriculture is to minimize the volume of herbicides that are applied to the fields through the use of site-specific weed management systems. In order to reach this goal, two major factors need to be considered: 1) the similar spectral signature, shape and texture between weeds and crops; 2) the irregular distribution of the weeds within the crop's field. This paper outlines an automatic computer vision system for the detection and differential spraying of Avena sterilis, a noxious weed growing in cereal crops. The proposed system involves two processes: image segmentation and decision making. Image segmentation combines basic suitable image processing techniques in order to extract cells from the image as the low level units. Each cell is described by two area-based attributes measuring the relations among the crops and the weeds. From these attributes, a hybrid decision making approach determines if a cell must be or not sprayed. The hybrid approach uses the Support Vector Machines and the Fuzzy k-Means methods, combined through the fuzzy aggregation theory. This makes the main finding of this paper. The method performance is compared against other available strategies.