Abstract: We present a simple nonconforming approximation of the linear two–point boundary value problem which violates patch test requirements. Nevertheless the solutions, obtained from these type of approximations, converge to the exact solution.
Abstract: This paper focuses on the data-driven generation
of fuzzy IF...THEN rules. The resulted fuzzy rule base can be
applied to build a classifier, a model used for prediction, or
it can be applied to form a decision support system. Among
the wide range of possible approaches, the decision tree and
the association rule based algorithms are overviewed, and two
new approaches are presented based on the a priori fuzzy
clustering based partitioning of the continuous input variables.
An application study is also presented, where the developed
methods are tested on the well known Wisconsin Breast Cancer
classification problem.
Abstract: Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
Abstract: In this paper, the generalized (2+1)-dimensional Calogero-Bogoyavlenskii-Schiff (shortly CBS) equations are investigated. We employ the Hirota-s bilinear method to obtain the bilinear form of CBS equations. Then by the idea of extended homoclinic test approach (shortly EHTA), some exact soliton solutions including breather type solutions are presented.
Abstract: One of the important applications of gas turbines is
their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for
determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance
data. For this reason a method was developed for determining the
exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable
error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is
based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General
Electric gas turbine design data for validation of methodologies. The
result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from
design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of
analyzer instruments, the method can be suitable alternative for gas
turbine standard performance test. In advance two methods are
proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between
the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the
method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.
Abstract: A kind of crash energy absorption structure adopted by vehicle simulator crash testing equipment based on mechanical energy
storage was studied. Dynamic explicit finite element simulation was achieved for thin-walled tube structure under different conditions of
section shape, thickness and inducement groove style. Crash energy absorption property of the structure was obtained. After optimization,
a reasonable structure was given which can meet current vehicle crash regulation. And the optimized structure can be adopted in vehicle
simulator, which can increase the practicability of the testing
equipment.
Abstract: This paper proposes method of diagnosing ball screw
preload loss through the Hilbert-Huang Transform （HHT） and
Multiscale entropy （MSE） process. The proposed method can
diagnose ball screw preload loss through vibration signals when the
machine tool is in operation. Maximum dynamic preload of 2 %, 4 %,
and 6 % ball screws were predesigned, manufactured, and tested
experimentally. Signal patterns are discussed and revealed using
Empirical Mode Decomposition（EMD）with the Hilbert Spectrum.
Different preload features are extracted and discriminated using HHT.
The irregularity development of a ball screw with preload loss is
determined and abstracted using MSE based on complexity
perception. Experiment results show that the proposed method can
predict the status of ball screw preload loss. Smart sensing for the
health of the ball screw is also possible based on a comparative
evaluation of MSE by the signal processing and pattern matching of
EMD/HHT. This diagnosis method realizes the purposes of prognostic
effectiveness on knowing the preload loss and utilizing convenience.
Abstract: A numerical method is proposed to calculate damping
properties for sound-proof structures involving elastic body,
viscoelastic body, and porous media. For elastic and viscoelastic body
displacement is modeled using conventional finite elements including
complex modulus of elasticity. Both effective density and bulk
modulus have complex quantities to represent damped sound fields in
the porous media. Particle displacement in the porous media is
discretised using finite element method. Displacement vectors as
common unknown variables are solved under coupled condition
between elastic body, viscoelastic body and porous media. Further,
explicit expressions of modal loss factor for the mixed structures are
derived using asymptotic method. Eigenvalue analysis and frequency
responded were calculated for automotive test panel laminated
viscoelastic and porous structures using this technique, the results
almost agreed with the experimental results.
Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.
Abstract: With the proliferation of Weblogs (blogs) use in
educational contexts, gaining a better understanding of why
students are willing to utilize blog systems has become an
important topic for practitioners and academics. While perceived
enjoyment has been found to have a significant influence on
behavioral intentions to use blogs or hedonic systems, few studies
have investigated the antecedents of perceived enjoyment in the
acceptance of blogging. The main purpose of the present study is to
explore the individual difference antecedents of perceived
enjoyment and examine how they influence behavioral intention to
blog through the mediation of perceived enjoyment. Based on the
previous literature, the Big Five personality traits (i.e.,
extraversion, agreeableness, conscientiousness, neuroticism, and
openness to experience), as well as computer self-efficacy and
personal innovation in information technology (PIIT), are
hypothesized as potential antecedents of perceived enjoyment in
the acceptance of blogging. Data collected from 358 respondents in
Taiwan are tested against the research model using the structural
equation modeling approach. The results indicate that extraversion,
agreeableness, conscientiousness, and PIIT have a significant
influence on perceived enjoyment, which in turn significantly
influences the behavioral intention to blog. These findings lead to
several important implications for future research.
Abstract: The relationship between different types of Molybdenum disulfide greases under extreme pressure loading and different speed situations have been studied using Design of Experiment (DOE) under 1200rpm steady state rotational speed and cyclic frequencies between 2400 and 1200rpm using a Plint machine software to set up the different rotational speed situations.
Research described here is aimed at providing good friction and wear performance while optimizing cyclic frequencies and MoS2 concentration due to the recent concern about grease behavior in extreme pressure applications. Extreme load of 785 Newton was used in conjunction with different cyclic frequencies (2400rpm -3.75min, 1200rpm -7.5min, 2400rpm -3.75min, 1200rpm -7.5min), to examine lithium based grease with and without MoS2 for equal number of revolutions, and a total run of 36000 revolutions; then compared to 1200rpm steady speed for the same total number of revolutions. 4 Ball wear tester was utilized to run large number of experiments randomly selected by the DOE software. The grease was combined with fine grade MoS2 or technical grade then heated to 750C and the wear scar width was collected at the end of each test. DOE model validation results verify that the data were very significant and can be applied to a wide range of extreme pressure applications. Based on simulation results and Scanning Electron images (SEM), it has been found that wear was largely dependent on the cyclic frequency condition. It is believed that technical grade MoS2 greases under faster cyclic speeds perform better and provides antiwear film that can resist extreme pressure loadings. Figures showed reduced wear scars width and improved frictional values.
Abstract: Recent research has shown that milk proteins can
yield bioactive peptides with opioid, mineral binding,
cytomodulatory, antihypertensive, immunostimulating, antimicrobial
and antioxidative activity in the human body. Bioactive peptides are
encrypted in milk proteins and are only released by enzymatic
hydrolysis in vivo during gastrointestinal digestion, food processing
or by microbial enzymes in fermented products. At present
significant research is being undertaken on the health effects of
bioactive peptides. A variety of naturally formed bioactive peptides
have been found in fermented dairy products, such as yoghurt, sour
milk and cheese. In particular, antihypertensive peptides have been
identified in fermented milks, whey and ripened cheese. Some of
these peptides have been commercialized in the form of fermented
milks. Bioactive peptides have the potential to be used in the
formulation of health-enhancing nutraceuticals, and as potent drugs
with well defined pharmacological effects.
Abstract: This paper proposes a neural network weights and
topology optimization using genetic evolution and the
backpropagation training algorithm. The proposed crossover and
mutation operators aims to adapt the networks architectures and
weights during the evolution process. Through a specific inheritance
procedure, the weights are transmitted from the parents to their
offsprings, which allows re-exploitation of the already trained
networks and hence the acceleration of the global convergence of the
algorithm. In the preprocessing phase, a new feature extraction
method is proposed based on Legendre moments with the Maximum
entropy principle MEP as a selection criterion. This allows a global
search space reduction in the design of the networks. The proposed
method has been applied and tested on the well known MNIST
database of handwritten digits.
Abstract: Design of a constant chord propeller is presented in
this paper in order to reduce propeller-s design procedure-s costs. The
design process was based on Lock and Goldstein-s techniques of
propeller design and analysis. In order to calculate optimum chord of
propeller, chord of a referential element is generalized as whole
blades chord. The design outcome which named CS-X-1 is modeled
& analyzed by CFD methods using K-ε: R.N.G turbulence model.
Convergence of results of two codes proved that outcome results of
design process are reliable. Design result is a two-blade propeller
with a total diameter of 1.1 meter, radial velocity of 3000 R.P.M,
efficiency above .75 and power coefficient near 1.05.
Abstract: Iris pattern is an important biological feature of human body; it becomes very hot topic in both research and practical applications. In this paper, an algorithm is proposed for iris recognition and a simple, efficient and fast method is introduced to extract a set of discriminatory features using first order gradient operator applied on grayscale images. The gradient based features are robust, up to certain extents, against the variations may occur in contrast or brightness of iris image samples; the variations are mostly occur due lightening differences and camera changes. At first, the iris region is located, after that it is remapped to a rectangular area of size 360x60 pixels. Also, a new method is proposed for detecting eyelash and eyelid points; it depends on making image statistical analysis, to mark the eyelash and eyelid as a noise points. In order to cover the features localization (variation), the rectangular iris image is partitioned into N overlapped sub-images (blocks); then from each block a set of different average directional gradient densities values is calculated to be used as texture features vector. The applied gradient operators are taken along the horizontal, vertical and diagonal directions. The low order norms of gradient components were used to establish the feature vector. Euclidean distance based classifier was used as a matching metric for determining the degree of similarity between the features vector extracted from the tested iris image and template features vectors stored in the database. Experimental tests were performed using 2639 iris images from CASIA V4-Interival database, the attained recognition accuracy has reached up to 99.92%.
Abstract: The aim of this study is to determine the basic information and communication technology (ICT) skills that may be needed by students studying in the 8th grade of the primary education in their cooperative project works implemented via the Internet. Within the scope of the study, the curriculum used for European Computer Driving License (ECDL) and the curriculum used in Turkey are also compared in terms of the ability to use ICT, which is aimed to be provided to the students. The research population of the study, during which the pre test – post test control group experimental model was used, consisted of 40 students from three different schools. In the first stage of the study, the skills that might be needed by students for their cooperative project works implemented via the Internet were determined through examination of the completed Comenious, e – twinning and WorldLinks projects. In the second stage of the study, the curriculums of the Turkish Ministry of National Education (MEB) and ECDL were evaluated by seven different teachers in line with these skills. Also in this study the ECDL and MEB curriculums were compared in terms of capability to provide the skills to implement cooperative projects via the Internet. In line with the findings of the study, the skills that might be needed by students to implement cooperative projects via the Internet were outlined, and existence of a significant difference was established in favor of the ECDL curriculum upon comparison of both curriculums in accordance with this outline (U = 50,500; p
Abstract: Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in cases that the words where chosen from a prespecified list.
Abstract: CO2 miscible displacement is not feasible in many oil fields due to high reservoir temperature as higher pressure is required to achieve miscibility. The miscibility pressure is far higher than the formation fracture pressure making it impossible to have CO2 miscible displacement. However, by using oleophilic chemicals, minimum miscibility pressure (MMP) could be lowered. The main objective of this research is to find the best oleophilic chemical in MMP reduction using slim-tube test and Vanishing Interfacial Tension (VIT) The chemicals are selected based on the characteristics that it must be oil soluble, low water solubility, have 4 – 8 carbons, semi polar, economical, and safe for human operation. The families of chemicals chosen are carboxylic acid, alcohol, and ketone. The whole experiment would be conducted at 100°C and the best chemical is said to be effective when it is able to lower CO2-crude oil MMP the most. Findings of this research would have great impact to the oil and gas industry in reduction of operation cost for CO2EOR which is applicable to both onshore and offshore operation.
Abstract: Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for Thyristor Controlled Series Compensator (TCSC)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller is formulated as an optimization problem and both the PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances, and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability.
Abstract: The purpose of this study was to investigate the effects of computer–based instructional designs, namely modality and redundancy principles on the attitude and learning of music theory among primary pupils of different Music Intelligence levels. The lesson of music theory was developed in three different modes, audio and image (AI), text with image (TI) and audio with image and text (AIT). The independent variables were the three modes of courseware. The moderator variable was music intelligence. The dependent variables were the post test score. ANOVA was used to determine the significant differences of the pretest scores among the three groups. Analyses of covariance (ANCOVA) and Post hoc were carried out to examine the main effects as well as the interaction effects of the independent variables on the dependent variables. High music intelligence pupils performed significantly better than low music intelligence pupils in all the three treatment modes. The AI mode was found to help pupils with low music intelligence significantly more than the TI and AIT modes.