Abstract: During last decades, developing multi-objective
evolutionary algorithms for optimization problems has found
considerable attention. Flexible job shop scheduling problem, as an
important scheduling optimization problem, has found this attention
too. However, most of the multi-objective algorithms that are
developed for this problem use nonprofessional approaches. In
another words, most of them combine their objectives and then solve
multi-objective problem through single objective approaches. Of
course, except some scarce researches that uses Pareto-based
algorithms. Therefore, in this paper, a new Pareto-based algorithm
called controlled elitism non-dominated sorting genetic algorithm
(CENSGA) is proposed for the multi-objective FJSP (MOFJSP). Our
considered objectives are makespan, critical machine work load, and
total work load of machines. The proposed algorithm is also
compared with one the best Pareto-based algorithms of the literature
on some multi-objective criteria, statistically.
Abstract: Nowadays, precipitation prediction is required for proper planning and management of water resources. Prediction with neural network models has received increasing interest in various research and application domains. However, it is difficult to determine the best neural network architecture for prediction since it is not immediately obvious how many input or hidden nodes are used in the model. In this paper, neural network model is used as a forecasting tool. The major aim is to evaluate a suitable neural network model for monthly precipitation mapping of Myanmar. Using 3-layerd neural network models, 100 cases are tested by changing the number of input and hidden nodes from 1 to 10 nodes, respectively, and only one outputnode used. The optimum model with the suitable number of nodes is selected in accordance with the minimum forecast error. In measuring network performance using Root Mean Square Error (RMSE), experimental results significantly show that 3 inputs-10 hiddens-1 output architecture model gives the best prediction result for monthly precipitation in Myanmar.
Abstract: Our objectives were to evaluate the effects of sire
breed, type of protein supplement, level of supplementation and sex
on wool spinning fineness (SF), its correlations with other wool
characteristics and prediction accuracy in F1 Merino crossbred lambs.
Texel, Coopworth, White Suffolk, East Friesian and Dorset rams
were mated with 500 purebred Merino dams at a ratio of 1:100 in
separate paddocks within a single management system. The F1
progeny were raised on ryegrass pasture until weaning, before forty
lambs were randomly allocated to treatments in a 5 x 2 x 2 x 2
factorial experimental design representing 5 sire breeds, 2
supplementary feeds (canola or lupins), 2 levels of supplementation
(1% or 2% of liveweight) and sex (wethers or ewes). Lambs were
supplemented for six weeks after an initial three weeks of adjustment,
wool sampled at the commencement and conclusion of the feeding
trial and analyzed for SF, mean fibre diameter (FD), coefficient of
variation (CV), standard deviation, comfort factor (CF), fibre
curvature (CURV), and clean fleece yield. Data were analyzed using
mixed linear model procedures with sire fitted as a random effect,
and sire breed, sex, supplementary feed type, level of
supplementation and their second-order interactions as fixed effects.
Sire breed (P
Abstract: In this study the integration of an absorption heat
pump (AHP) with the concentration section of an industrial pulp and
paper process is investigated using pinch technology. The optimum
design of the proposed water-lithium bromide AHP is then achieved
by minimizing the total annual cost. A comprehensive optimization is
carried out by relaxation of all stream pressure drops as well as heat
exchanger areas involving in AHP structure. It is shown that by
applying genetic algorithm optimizer, the total annual cost of the
proposed AHP is decreased by 18% compared to one resulted from
simulation.
Abstract: We develop a three-step fuzzy logic-based algorithm for clustering categorical attributes, and we apply it to analyze cultural data. In the first step the algorithm employs an entropy-based clustering scheme, which initializes the cluster centers. In the second step we apply the fuzzy c-modes algorithm to obtain a fuzzy partition of the data set, and the third step introduces a novel cluster validity index, which decides the final number of clusters.
Abstract: A local municipality has decided to build a sewage pit
to receive residential sewage waste arriving by tank trucks. Daily
accumulated waste are to be pumped to a nearby waste water
treatment facility to be re-consumed for agricultural and construction
projects. A discrete-event simulation model using Arena Software
was constructed to assist in defining the capacity of the system in
cubic meters, number of tank trucks to use the system, number of
unload docks required, number of standby areas needed and
manpower required for data collection at entrance checkpoint and
truck tank load toxicity testing. The results of the model are
statistically validated. Simulation turned out to be an excellent tool
in the facility planning effort for the pit project, as it insured smooth
flow lines of tank trucks load discharge and best utilization of
facilities on site.
Abstract: In this paper, an automatic determination algorithm for nuclear magnetic resonance (NMR) spectra of the metabolites in the living body by magnetic resonance spectroscopy (MRS) without human intervention or complicated calculations is presented. In such method, the problem of NMR spectrum determination is transformed into the determination of the parameters of a mathematical model of the NMR signal. To calculate these parameters efficiently, a new model called modified Hopfield neural network is designed. The main achievement of this paper over the work in literature [30] is that the speed of the modified Hopfield neural network is accelerated. This is done by applying cross correlation in the frequency domain between the input values and the input weights. The modified Hopfield neural network can accomplish complex dignals perfectly with out any additinal computation steps. This is a valuable advantage as NMR signals are complex-valued. In addition, a technique called “modified sequential extension of section (MSES)" that takes into account the damping rate of the NMR signal is developed to be faster than that presented in [30]. Simulation results show that the calculation precision of the spectrum improves when MSES is used along with the neural network. Furthermore, MSES is found to reduce the local minimum problem in Hopfield neural networks. Moreover, the performance of the proposed method is evaluated and there is no effect on the performance of calculations when using the modified Hopfield neural networks.
Abstract: Pressure waves and Water Hammer occur in a
pumping system when valves are closed or opened suddenly or in
the case of sudden failure of pumps. Determination of maximum
water hammer is considered one of the most important technical
and economical items of which engineers and designers of
pumping stations and conveyance pipelines should take care.
Hammer Software is a recent application used to simulate water
hammer. The present study focuses on determining significance of
each input parameter of the application relative to the maximum
amount of water hammer estimated by the software. The study
determines estimated maximum water hammer variations due to
variations of input parameters including water temperature, pipe
type, thickness and diameter, electromotor rpm and power, and
moment of inertia of electromotor and pump. In our study,
Kuhrang Pumping Station was modeled using WaterGEMS
Software. The pumping station is characterized by total discharge
of 200 liters per second, dynamic height of 194 meters and 1.5
kilometers of steel conveyance pipeline and transports water to
Cheshme Morvarid for farmland irrigation. The model was run in
steady hydraulic condition and transferred to Hammer Software.
Then, the model was run in several unsteady hydraulic conditions
and sensitivity of maximum water hammer to each input parameter
was calculated. It is shown that parameters to which maximum
water hammer is most sensitive are moment of inertia of pump and
electromotor, diameter, type and thickness of pipe and water
temperature, respectively.
Abstract: Virtual touch screen using camera is an ordinary screen which uses a camera to imitate the touch screen by taking a picture of an indicator, e.g., finger, which is laid on the screen, converting the indicator tip position on the picture to the position on the screen, and moving the cursor on the screen to that position. In fact, the indicator is not laid on the screen directly, but it is intervened by the cover at some intervals. In spite of this gap, if the eye-indicator-camera angle is not large, the mapping from the indicator tip positions on the image to the corresponding cursor positions on the screen is not difficult and could be done with a little error. However, the larger the angle is, the bigger the error in the mapping occurs. This paper proposes cursor position estimation model for virtual touch screen using camera which could eliminate this kind of error. The proposed model (i) moves the on-screen pilot cursor to the screen position which locates on the screen at the position just behind the indicator tip when the indicator tip has been looked from the camera position, and then (ii) converts that pilot cursor position to the desirable cursor position (the position on the screen when it has been looked from the user-s eye through the indicator tip) by using the bilinear transformation. Simulation results show the correctness of the estimated cursor position by using the proposed model.
Abstract: E-Learning systems are used by many learners and
teachers. The developer is developing the e-Learning system. However,
the developer cannot do system construction to satisfy all of
users- demands. We discuss a method of constructing e-Learning
systems where learners and teachers can design, try to use, and share
extending system functions that they want to use; which may be nally
added to the system by system managers.
Abstract: This study reports results of a meta-analytic path analysis e-learning Acceptance Model with k = 27 studies, Databases searched included Information Sciences Institute (ISI) website. Variables recorded included perceived usefulness, perceived ease of use, attitude toward behavior, and behavioral intention to use e-learning. A correlation matrix of these variables was derived from meta-analytic data and then analyzed by using structural path analysis to test the fitness of the e-learning acceptance model to the observed aggregated data. Results showed the revised hypothesized model to be a reasonable, good fit to aggregated data. Furthermore, discussions and implications are given in this article.
Abstract: The electrical interaction between two axisymmetric
spheroidal particles in an electrolyte solution is examined numerically.
A Galerkin finite element method combined with a Newton-Raphson
iteration scheme is proposed to evaluate the spatial variation in the
electrical potential, and the result obtained used to estimate the
interaction energy between two particles. We show that if the surface
charge density is fixed, the potential gradient is larger at a point, which
has a larger curvature, and if surface potential is fixed, surface charge
density is proportional to the curvature. Also, if the total interaction
energy against closest surface-to-surface curve exhibits a primary
maximum, the maximum follows the order (oblate-oblate) >
(sphere-sphere)>(oblate-prolate)>(prolate-prolate), and if the curve
has a secondary minimum, the absolute value of the minimum follows
the same order.
Abstract: The use of Inverse Discrete Fourier Transform (IDFT) implemented in the form of Inverse Fourier Transform (IFFT) is one of the standard method of reconstructing Magnetic Resonance Imaging (MRI) from uniformly sampled K-space data. In this tutorial, three of the major problems associated with the use of IFFT in MRI reconstruction are highlighted. The tutorial also gives brief introduction to MRI physics; MRI system from instrumentation point of view; K-space signal and the process of IDFT and IFFT for One and two dimensional (1D and 2D) data.
Abstract: One very interesting field of research in Pattern Recognition that has gained much attention in recent times is Gesture Recognition. In this paper, we consider a form of dynamic hand gestures that are characterized by total movement of the hand (arm) in space. For these types of gestures, the shape of the hand (palm) during gesturing does not bear any significance. In our work, we propose a model-based method for tracking hand motion in space, thereby estimating the hand motion trajectory. We employ the dynamic time warping (DTW) algorithm for time alignment and normalization of spatio-temporal variations that exist among samples belonging to the same gesture class. During training, one template trajectory and one prototype feature vector are generated for every gesture class. Features used in our work include some static and dynamic motion trajectory features. Recognition is accomplished in two stages. In the first stage, all unlikely gesture classes are eliminated by comparing the input gesture trajectory to all the template trajectories. In the next stage, feature vector extracted from the input gesture is compared to all the class prototype feature vectors using a distance classifier. Experimental results demonstrate that our proposed trajectory estimator and classifier is suitable for Human Computer Interaction (HCI) platform.
Abstract: The Kansei engineering is a technology which
converts human feelings into quantitative terms and helps designers
develop new products that meet customers- expectation. Standard
Kansei engineering procedure involves finding relationships between
human feelings and design elements of which many researchers have
found forward and backward relationship through various soft
computing techniques. In this paper, we proposed the framework of
Kansei engineering linking relationship not only between human
feelings and design elements, but also the whole part of product, by
constructing association rules. In this experiment, we obtain input
from emotion score that subjects rate when they see the whole part of
the product by applying semantic differentials. Then, association
rules are constructed to discover the combination of design element
which affects the human feeling. The results of our experiment
suggest the pattern of relationship of design elements according to
human feelings which can be derived from the whole part of product.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: In this paper, the dam-reservoir interaction is
analyzed using a finite element approach. The fluid is assumed to be
incompressible, irrotational and inviscid. The assumed boundary
conditions are that the interface of the dam and reservoir is vertical
and the bottom of reservoir is rigid and horizontal. The governing
equation for these boundary conditions is implemented in the
developed finite element code considering the horizontal and vertical
earthquake components. The weighted residual standard Galerkin
finite element technique with 8-node elements is used to discretize
the equation that produces a symmetric matrix equation for the damreservoir
system. A new boundary condition is proposed for
truncating surface of unbounded fluid domain to show the energy
dissipation in the reservoir, through radiation in the infinite upstream
direction. The Sommerfeld-s and perfect damping boundary
conditions are also implemented for a truncated boundary to compare
with the proposed far end boundary. The results are compared with
an analytical solution to demonstrate the accuracy of the proposed
formulation and other truncated boundary conditions in modeling the
hydrodynamic response of an infinite reservoir.
Abstract: Background, measuring an individual-s Health
Literacy is gaining attention, yet no appropriate instrument is available
in Taiwan. Measurement tools that were developed and used in
western countries may not be appropriate for use in Taiwan due to a
different language system. Purpose of this research was to develop a
Health Literacy measurement instrument specific for Taiwan adults.
Methods, several experts of clinic physicians; healthcare
administrators and scholars identified 125 common used health related
Chinese phrases from major medical knowledge sources that easy
accessible to the public. A five-point Likert scale is used to measure
the understanding level of the target population. Such measurement is
then used to compare with the correctness of their answers to a health
knowledge test for validation. Samples, samples under study were
purposefully taken from four groups of people in the northern
Pingtung, OPD patients, university students, community residents,
and casual visitors to the central park. A set of health knowledge index
with 10 questions is used to screen those false responses. A sample
size of 686 valid cases out of 776 was then included to construct this
scale. An independent t-test was used to examine each individual
phrase. The phrases with the highest significance are then identified
and retained to compose this scale. Result, a Taiwan Health Literacy
Scale (THLS) was finalized with 66 health-related phrases under nine
divisions. Cronbach-s alpha of each division is at a satisfactory level
of 89% and above. Conclusions, factors significantly differentiate the
levels of health literacy are education, female gender, age, family
members of stroke victims, experience with patient care, and
healthcare professionals in the initial application in this study..
Abstract: Outlier detection in streaming data is very challenging because streaming data cannot be scanned multiple times and also new concepts may keep evolving. Irrelevant attributes can be termed as noisy attributes and such attributes further magnify the challenge of working with data streams. In this paper, we propose an unsupervised outlier detection scheme for streaming data. This scheme is based on clustering as clustering is an unsupervised data mining task and it does not require labeled data, both density based and partitioning clustering are combined for outlier detection. In this scheme partitioning clustering is also used to assign weights to attributes depending upon their respective relevance and weights are adaptive. Weighted attributes are helpful to reduce or remove the effect of noisy attributes. Keeping in view the challenges of streaming data, the proposed scheme is incremental and adaptive to concept evolution. Experimental results on synthetic and real world data sets show that our proposed approach outperforms other existing approach (CORM) in terms of outlier detection rate, false alarm rate, and increasing percentages of outliers.
Abstract: In this paper we focus on event extraction from Tamil
news article. This system utilizes a scoring scheme for extracting and
grouping event-specific sentences. Using this scoring scheme eventspecific
clustering is performed for multiple documents. Events are
extracted from each document using a scoring scheme based on
feature score and condition score. Similarly event specific sentences
are clustered from multiple documents using this scoring scheme.
The proposed system builds the Event Template based on user
specified query. The templates are filled with event specific details
like person, location and timeline extracted from the formed clusters.
The proposed system applies these methodologies for Tamil news
articles that have been enconverted into UNL graphs using a Tamil to
UNL-enconverter. The main intention of this work is to generate an
event based template.