Abstract: This study introduces a new method for detecting,
sorting, and localizing spikes from multiunit EEG recordings. The
method combines the wavelet transform, which localizes distinctive
spike features, with Super-Paramagnetic Clustering (SPC) algorithm,
which allows automatic classification of the data without assumptions
such as low variance or Gaussian distributions. Moreover, the method
is capable of setting amplitude thresholds for spike detection. The
method makes use of several real EEG data sets, and accordingly the
spikes are detected, clustered and their times were detected.
Abstract: The main goal in this paper is to quantify the quality of
different techniques for radiation treatment plans, a back-propagation
artificial neural network (ANN) combined with biomedicine theory
was used to model thirteen dosimetric parameters and to calculate
two dosimetric indices. The correlations between dosimetric indices
and quality of life were extracted as the features and used in the ANN
model to make decisions in the clinic. The simulation results show
that a trained multilayer back-propagation neural network model can
help a doctor accept or reject a plan efficiently. In addition, the
models are flexible and whenever a new treatment technique enters
the market, the feature variables simply need to be imported and the
model re-trained for it to be ready for use.
Abstract: Air bending is one of the important metal forming
processes, because of its simplicity and large field application.
Accuracy of analytical and empirical models reported for the analysis
of bending processes is governed by simplifying assumption and do
not consider the effect of dynamic parameters. Number of researches
is reported on the finite element analysis (FEA) of V-bending, Ubending,
and air V-bending processes. FEA of bending is found to be
very sensitive to many physical and numerical parameters. FE
models must be computationally efficient for practical use. Reported
work shows the 3D FEA of air bending process using Hyperform LSDYNA
and its comparison with, published 3D FEA results of air
bending in Ansys LS-DYNA and experimental results. Observing the
planer symmetry and based on the assumption of plane strain
condition, air bending problem was modeled in 2D with symmetric
boundary condition in width. Stress-strain results of 2D FEA were
compared with 3D FEA results and experiments. Simplification of
air bending problem from 3D to 2D resulted into tremendous
reduction in the solution time with only marginal effect on stressstrain
results. FE model simplification by studying the problem
symmetry is more efficient and practical approach for solution of
more complex large dimensions slow forming processes.
Abstract: Many non-conventional adsorbent have been studied
as economic alternative to commercial activated carbon and mostly
agricultural waste have been introduced such as rubber leaf powder
and hazelnut shell. Microwave Incinerated Rice Husk Ash
(MIRHA), produced from the rice husk is one of the low-cost
materials that were used as adsorbent of heavy metal. The aim of
this research was to study the feasibility of using MIRHA500 and
MIRHA800 as adsorbent for the removal of Cu(II) metal ions from
aqueous solutions by the batch studies. The adsorption of Cu(II) into
MIRHA500 and MIRH800 favors Fruendlich isotherm and imply
pseudo – kinetic second order which applied chemisorptions
Abstract: Air bubbles have been detected in human circulation
of end-stage renal disease patients who are treated by hemodialysis.
The consequence of air embolism, air bubbles, is under recognized
and usually overlooked in daily practice. This paper shows results of
a capacitor based detection method that capable of detecting the
presence of air bubbles in the blood stream in different frequencies.
The method is based on a parallel plates capacitor made of platinum
with an area of 1.5 cm2 and a distance between the two plates is 1cm.
The dielectric material used in this capacitor is Dextran70 solution
which mimics blood rheology. Simulations were carried out using
RC circuit at two frequencies 30Hz and 3 kHz and results compared
with experiments and theory. It is observed that by injecting air
bubbles of different diameters into the device, there were significant
changes in the capacitance of the capacitor. Furthermore, it is
observed that the output voltage from the circuit increased with
increasing air bubble diameter. These results demonstrate the
feasibility of this approach in improving air bubble detection in
Hemodialysis.
Abstract: The rapid growth of e-Commerce services is
significantly observed in the past decade. However, the method to
verify the authenticated users still widely depends on numeric
approaches. A new search on other verification methods suitable for
online e-Commerce is an interesting issue. In this paper, a new online
signature-verification method using angular transformation is
presented. Delay shifts existing in online signatures are estimated by
the estimation method relying on angle representation. In the
proposed signature-verification algorithm, all components of input
signature are extracted by considering the discontinuous break points
on the stream of angular values. Then the estimated delay shift is
captured by comparing with the selected reference signature and the
error matching can be computed as a main feature used for verifying
process. The threshold offsets are calculated by two types of error
characteristics of the signature verification problem, False Rejection
Rate (FRR) and False Acceptance Rate (FAR). The level of these two
error rates depends on the decision threshold chosen whose value is
such as to realize the Equal Error Rate (EER; FAR = FRR). The
experimental results show that through the simple programming,
employed on Internet for demonstrating e-Commerce services, the
proposed method can provide 95.39% correct verifications and 7%
better than DP matching based signature-verification method. In
addition, the signature verification with extracting components
provides more reliable results than using a whole decision making.
Abstract: It is difficult to judge ripeness by outward
characteristics such as size or external color. In this paper a nondestructive
method was studied to determine watermelon (Crimson
Sweet) quality. Responses of samples to excitation vibrations were
detected using laser Doppler vibrometry (LDV) technology. Phase
shift between input and output vibrations were extracted overall
frequency range. First and second were derived using frequency
response spectrums. After nondestructive tests, watermelons were
sensory evaluated. So the samples were graded in a range of ripeness
based on overall acceptability (total desired traits consumers).
Regression models were developed to predict quality using obtained
results and sample mass. The determination coefficients of the
calibration and cross validation models were 0.89 and 0.71
respectively. This study demonstrated feasibility of information
which is derived vibration response curves for predicting fruit
quality. The vibration response of watermelon using the LDV method
is measured without direct contact; it is accurate and timely, which
could result in significant advantage for classifying watermelons
based on consumer opinions.
Abstract: The aim of this study is to emphasize the opportunities in space design under the aspect of HCI as performance areas. HCI is a multidisciplinary approach that could be identified in many different areas. The aesthetical reflections of HCI by virtual reality in space design are the high-tech solutions of the new innovations as computational facilities by artistic features. The method of this paper is to identify the subject in 3 main parts. In the first part a general approach and definition of interactivity on the basis of space design; in the second part the concept of multimedia interactive theater by some chosen samples from the world and interactive design aspects; in the third part the samples from Turkey will be identified by stage designing principles. In the results it could be declared that the multimedia database is the virtual approach of theatre stage designing regarding interactive means by computational facilities according to aesthetical aspects. HCI is mostly identified in theatre stages as computational intelligence under the affect of interactivity.
Abstract: This paper considers the influence of promotion
instruments for renewable energy sources (RES) on a multi-energy
modeling framework. In Europe, so called Feed-in Tariffs are
successfully used as incentive structures to increase the amount of
energy produced by RES. Because of the stochastic nature of large
scale integration of distributed generation, many problems have
occurred regarding the quality and stability of supply. Hence, a
macroscopic model was developed in order to optimize the power
supply of the local energy infrastructure, which includes electricity,
natural gas, fuel oil and district heating as energy carriers. Unique
features of the model are the integration of RES and the adoption of
Feed-in Tariffs into one optimization stage. Sensitivity studies are
carried out to examine the system behavior under changing profits
for the feed-in of RES. With a setup of three energy exchanging
regions and a multi-period optimization, the impact of costs and
profits are determined.
Abstract: Hybrid knowledge model is suggested as an underlying
framework for product development management. It can support such
hybrid features as ontologies and rules. Effective collaboration in
product development environment depends on sharing and reasoning
product information as well as engineering knowledge. Many studies
have considered product information and engineering knowledge.
However, most previous research has focused either on building the
ontology of product information or rule-based systems of engineering
knowledge. This paper shows that F-logic based knowledge model can
support such desirable features in a hybrid way.
Abstract: In the visual servoing systems, the data obtained by
Visionary is used for controlling robots. In this project, at first the
simulator which was proposed for simulating the performance of a
6R robot before, was examined in terms of software and test, and in
the proposed simulator, existing defects were obviated. In the first
version of simulation, the robot was directed toward the target object only in a Position-based method using two cameras in the
environment. In the new version of the software, three cameras were used simultaneously. The camera which is installed as eye-inhand on the end-effector of the robot is used for visual servoing in a
Feature-based method. The target object is recognized according to
its characteristics and the robot is directed toward the object in compliance with an algorithm similar to the function of human-s
eyes. Then, the function and accuracy of the operation of the robot are examined through Position-based visual servoing method using
two cameras installed as eye-to-hand in the environment. Finally, the obtained results are tested under ANSI-RIA R15.05-2 standard.
Abstract: The new idea of this research is application of a new fault detection and isolation (FDI) technique for supervision of sensor networks in transportation system. In measurement systems, it is necessary to detect all types of faults and failures, based on predefined algorithm. Last improvements in artificial neural network studies (ANN) led to using them for some FDI purposes. In this paper, application of new probabilistic neural network features for data approximation and data classification are considered for plausibility check in temperature measurement. For this purpose, two-phase FDI mechanism was considered for residual generation and evaluation.
Abstract: The application of Neural Network for disease
diagnosis has made great progress and is widely used by physicians.
An Electrocardiogram carries vital information about heart activity and physicians use this signal for cardiac disease diagnosis which
was the great motivation towards our study. In our work, tachycardia
features obtained are used for the training and testing of a Neural
Network. In this study we are using Fuzzy Probabilistic Neural
Networks as an automatic technique for ECG signal analysis. As
every real signal recorded by the equipment can have different
artifacts, we needed to do some preprocessing steps before feeding it
to our system. Wavelet transform is used for extracting the
morphological parameters of the ECG signal. The outcome of the
approach for the variety of arrhythmias shows the represented
approach is superior than prior presented algorithms with an average
accuracy of about %95 for more than 7 tachy arrhythmias.
Abstract: Object Relational Databases (ORDB) are complex in
nature than traditional relational databases because they combine the
characteristics of both object oriented concepts and relational
features of conventional databases. Design of an ORDB demands
efficient and quality schema considering the structural, functional
and componential traits. This internal quality of the schema is
assured by metrics that measure the relevant attributes. This is
extended to substantiate the understandability, usability and
reliability of the schema, thus assuring external quality of the
schema. This work institutes a formalization of ORDB metrics;
metric definition, evaluation methodology and the calibration of the
metric. Three ORDB schemas were used to conduct the evaluation
and the formalization of the metrics. The metrics are calibrated using
content and criteria related validity based on the measurability,
consistency and reliability of the metrics. Nominal and summative
scales are derived based on the evaluated metric values and are
standardized. Future works pertaining to ORDB metrics forms the
concluding note.
Abstract: A theory for optimal filtering of infinite sets of random
signals is presented. There are several new distinctive features of the
proposed approach. First, a single optimal filter for processing any
signal from a given infinite signal set is provided. Second, the filter is
presented in the special form of a sum with p terms where each term
is represented as a combination of three operations. Each operation
is a special stage of the filtering aimed at facilitating the associated
numerical work. Third, an iterative scheme is implemented into the
filter structure to provide an improvement in the filter performance at
each step of the scheme. The final step of the scheme concerns signal
compression and decompression. This step is based on the solution of
a new rank-constrained matrix approximation problem. The solution
to the matrix problem is described in this paper. A rigorous error
analysis is given for the new filter.
Abstract: This article presents a short discussion on
optimum neighborhood size selection in a spherical selforganizing
feature map (SOFM). A majority of the literature
on the SOFMs have addressed the issue of selecting optimal
learning parameters in the case of Cartesian topology SOFMs.
However, the use of a Spherical SOFM suggested that the
learning aspects of Cartesian topology SOFM are not directly
translated. This article presents an approach on how to
estimate the neighborhood size of a spherical SOFM based on
the data. It adopts the L-curve criterion, previously suggested
for choosing the regularization parameter on problems of
linear equations where their right-hand-side is contaminated
with noise. Simulation results are presented on two artificial
4D data sets of the coupled Hénon-Ikeda map.
Abstract: Solar Cells are destined to supply electric energy beginning from primary resources. It can charge a battery up to 12V dc. For residential use an inverter for 12V dc to 220Vac conversion is desired. For this a static DC-AC converter is necessarily inserted between the solar cells and the distribution network. This paper describes a new P.W.M. strategy for a voltage source inverter. This modulation strategy reduces the energy losses and harmonics in the P.W.M. voltage source inverter. This technique allows the P.W.M. voltage source inverter to become a new feasible solution for solar home application.
Abstract: Microtomographic images and thin section (TS)
images were analyzed and compared against some parameters of
geological interest such as porosity and its distribution along the
samples. The results show that microtomography ( CT) analysis,
although limited by its resolution, have some interesting information
about the distribution of porosity (homogeneous or not) and can also
quantify the connected and non-connected pores, i.e., total porosity.
TS have no limitations concerning resolution, but are limited by the
experimental data available in regards to a few glass sheets for
analysis and also can give only information about the connected
pores, i.e., effective porosity. Those two methods have their own
virtues and flaws but when paired together they are able to
complement one another, making for a more reliable and complete
analysis.
Abstract: A subsea hydrocarbon production system can undergo planned and unplanned shutdowns during the life of the field. The thermal FEA is used to simulate the cool down to verify the insulation design of the subsea equipment, but it is also used to derive an acceptable insulation design for the cold spots. The driving factors of subsea analyses require fast responding and accurate models of the equipment cool down. This paper presents cool down analysis carried out by a Krylov subspace reduction method, and compares this approach to the commonly used FEA solvers. The model considered represents a typical component of a subsea production system, a closed valve on a dead leg. The results from the Krylov reduction method exhibits the least error and requires the shortest computational time to reach the solution. These findings make the Krylov model order reduction method very suitable for the above mentioned subsea applications.
Abstract: This is an applied research to propose the method for
price quotation for a contract electronics manufacturer. It has had a
precise price quoting method but such method could not quickly
provide a result as the customer required. This reduces the ability of
company to compete in this kind of business. In this case, the cause
of long time quotation process was analyzed. A lot of product
features have been demanded by customer. By checking routine
processes, it was found that high fraction of quoting time was used
for production time estimating which has effected to the
manufacturing or production cost. Then the historical data of
products including types, number of components, assembling
method, and their assembling time were used to analyze the key
components affecting to production time. The price quoting model
then was proposed. The implementation of proposed model was able
to remarkably reduce quoting time with an acceptable required
precision.