Abstract: Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrollments of the University of Alabama. In recent years, a number of techniques have been proposed for forecasting based on fuzzy set theory methods. These methods have either used enrollment numbers or differences of enrollments as the universe of discourse. We propose using the year to year percentage change as the universe of discourse. In this communication, the approach of Jilani, Burney, and Ardil is modified by using the year to year percentage change as the universe of discourse. We use enrollment figures for the University of Alabama to illustrate our proposed method. The proposed method results in better forecasting accuracy than existing models.
Abstract: Growing world population has fundamental impacts
and often catastrophic on natural habitat. The immethodical
consumption of energy, destruction of the forests and extinction of
plant and animal species are the consequence of this experience.
Urban sustainability and sustainable urban development, that is so
spoken these days, should be considered as a strategy, goal and
policy, beyond just considering environmental issues and protection.
The desert-s climate has made a bunch of problems for its residents.
Very hot and dry climate in summers of the Iranian desert areas,
when there was no access to modern energy source and mechanical
cooling systems in the past, made Iranian architects to design a
natural ventilation system in their buildings. The structure, like a
tower going upward the roof, besides its ornamental application and
giving a beautiful view to the building, was used as a spontaneous
ventilation system. In this paper, it has been tried to name the
problems of the area and it-s inconvenience, then some answers has
pointed out in order to solve the problems and as an alternative
solution BADGIR (wind-catcher) has been introduced as a solution
knowing that it has been playing a major role in dealing with the
problems.
Abstract: It is essential to have a uniform and calm flow field
for a settling tank to have high performance. In general, the
recirculation zones always occurred in sedimentation tanks. The
presence of these regions may have different effects. The nonuniformity
of the velocity field, the short-circuiting at the surface and
the motion of the jet at the bed of the tank that occurs because of the
recirculation in the sedimentation layer, are affected by the geometry
of the tank. There are some ways to decrease the size of these dead
zones, which would increase the performance. One of the ways is to
use a suitable baffle configuration. In this study, the presence of
baffle with different position has been investigated by a finite volume
method, with VOF (Volume of Fluid) model. Besides, the k-ε
turbulence model is used in the numerical calculations. The results
indicate that the best position of the baffle is obtained when the
volume of the recirculation region is minimized or is divided to
smaller part and the flow field trend to be uniform in the settling
zone.
Abstract: The distinction among urban, periurban and rural areas represents a classical example of uncertainty in land classification. Satellite images, geostatistical analysis and all kinds of spatial data are very useful in urban sprawl studies, but it is important to define precise rules in combining great amounts of data to build complex knowledge about territory. Rough Set theory may be a useful method to employ in this field. It represents a different mathematical approach to uncertainty by capturing the indiscernibility. Two different phenomena can be indiscernible in some contexts and classified in the same way when combining available information about them. This approach has been applied in a case of study, comparing the results achieved with both Map Algebra technique and Spatial Rough Set. The study case area, Potenza Province, is particularly suitable for the application of this theory, because it includes 100 municipalities with different number of inhabitants and morphologic features.
Abstract: Among the chemicals used for ammunition production, TNT (Trinitrotoluene) play a significant role since World War I and II. Various types of military weapon utilize TNT in casting process. However, the TNT casting process for warhead is difficult to control the cooling rate of the liquid TNT. This problem occurs because the casting process lacks the equipment to detect the temperature during the casting procedure This study presents the temperature detected by infrared camera to illustrate the cooling rate and cooling zone of curing, and demonstrates the optimization of TNT condition to reduce the risk of air gap occurred in the warhead which can result in the destruction afterward. Premature initiation of explosive-filled projectiles in response to set-back forces during gunfiring cause by casting defects. Finally the study can help improving the process of the TNT casting. The operators can control the curing of TNT inside the case by rising up the heating rod at the proper time. Consequently this can reduce tremendous time of rework if the air gaps occur and increase strength to lower elastic modulus. Therefore, it can be clearly concluded that the use of Infrared Cameras in this process is another method to improve the casting procedure.
Abstract: In this paper we propose a robust environmental sound classification approach, based on spectrograms features driven from log-Gabor filters. This approach includes two methods. In the first methods, the spectrograms are passed through an appropriate log-Gabor filter banks and the outputs are averaged and underwent an optimal feature selection procedure based on a mutual information criteria. The second method uses the same steps but applied only to three patches extracted from each spectrogram.
To investigate the accuracy of the proposed methods, we conduct experiments using a large database containing 10 environmental sound classes. The classification results based on Multiclass Support Vector Machines show that the second method is the most efficient with an average classification accuracy of 89.62 %.
Abstract: The objective of this article is to discuss the potential
of economic analysis as a tool for identification and evaluation of
corruption in legislative acts. We propose that corruption be
perceived as a risk variable within the legislative process. Therefore
we find it appropriate to employ risk analysis methods, used in
various fields of economics, for the evaluation of corruption in
legislation. Furthermore we propose the incorporation of these
methods into the so called corruption impact assessment (CIA), the
general framework for detection of corruption in legislative acts. The
applications of the risk analysis methods are demonstrated on
examples of implementation of proposed CIA in the Czech Republic.
Abstract: Monitoring lightning electromagnetic pulses (sferics)
and other terrestrial as well as extraterrestrial transient radiation signals
is of considerable interest for practical and theoretical purposes
in astro- and geophysics as well as meteorology. Managing a continuous
flow of data, automisation of the detection and classification
process is important. Features based on a combination of wavelet and
statistical methods proved efficient for analysis and characterisation
of transients and as input into a radial basis function network that is
trained to discriminate transients from pulse like to wave like.
Abstract: This paper presents a method for functional projective H∞ synchronization problem of chaotic systems with external disturbance. Based on Lyapunov theory and linear matrix inequality (LMI) formulation, the novel feedback controller is established to not only guarantee stable synchronization of both drive and response systems but also reduce the effect of external disturbance to an H∞ norm constraint.
Abstract: This paper discusses a genetic algorithm (GA) based optimal load shedding that can apply for electrical distribution networks with and without dispersed generators (DG). Also, the proposed method has the ability for considering constant and variable capacity deficiency caused by unscheduled outages in the bulked generation and transmission system of bulked power supply. The genetic algorithm (GA) is employed to search for the optimal load shedding strategy in distribution networks considering DGs in two cases of constant and variable modelling of bulked power supply of distribution networks. Electrical power distribution systems have a radial network and unidirectional power flows. With the advent of dispersed generations, the electrical distribution system has a locally looped network and bidirectional power flows. Therefore, installed DG in the electrical distribution systems can cause operational problems and impact on existing operational schemes. Introduction of DGs in electrical distribution systems has introduced many new issues in operational and planning level. Load shedding as one of operational issue has no exempt. The objective is to minimize the sum of curtailed load and also system losses within the frame-work of system operational and security constraints. The proposed method is tested on a radial distribution system with 33 load points for more practical applications.
Abstract: The information revealed by derivatives can help to
better characterize digital near-end crosstalk signatures with the
ultimate goal of identifying the specific aggressor signal.
Unfortunately, derivatives tend to be very sensitive to even low
levels of noise. In this work we approximated the derivatives of both
quiet and noisy digital signals using a wavelet-based technique. The
results are presented for Gaussian digital edges, IBIS Model digital
edges, and digital edges in oscilloscope data captured from an actual
printed circuit board. Tradeoffs between accuracy and noise
immunity are presented. The results show that the wavelet technique
can produce first derivative approximations that are accurate to
within 5% or better, even under noisy conditions. The wavelet
technique can be used to calculate the derivative of a digital signal
edge when conventional methods fail.
Abstract: The nature of consumer products causes the difficulty
in forecasting the future demands and the accuracy of the forecasts
significantly affects the overall performance of the supply chain
system. In this study, two data mining methods, artificial neural
network (ANN) and support vector machine (SVM), were utilized to
predict the demand of consumer products. The training data used was
the actual demand of six different products from a consumer product
company in Thailand. The results indicated that SVM had a better
forecast quality (in term of MAPE) than ANN in every category of
products. Moreover, another important finding was the margin
difference of MAPE from these two methods was significantly high
when the data was highly correlated.
Abstract: Classifier fusion may generate more accurate
classification than each of the basic classifiers. Fusion is often based
on fixed combination rules like the product, average etc. This paper
presents decision templates as classifier fusion method for the
recognition of the handwritten English and Farsi numerals (1-9).
The process involves extracting a feature vector on well-known
image databases. The extracted feature vector is fed to multiple
classifier fusion. A set of experiments were conducted to compare
decision templates (DTs) with some combination rules. Results from
decision templates conclude 97.99% and 97.28% for Farsi and
English handwritten digits.
Abstract: A simple method for the simultaneous determination
of hippuric acid and benzoic acid in urine using reversed-phase high
performance liquid chromatography was described. Chromatography
was performed on a Nova-Pak C18 (3.9 x 150 mm) column with a
mobile phase of mixed solution methanol: water: acetic acid
(20:80:0.2) and UV detection at 254 nm. The calibration curve was
linear within concentration range at 0.125 to 6.0 mg/ml of hippuric
acid and benzoic acid. The recovery, accuracy and coefficient
variance of hippuric acid were 104.54%, 0.2% and 0.2% respectively
and for benzoic acid were 98.48%, 1.25% and 0.60% respectively.
The detection limit of this method was 0.01ng/l for hippuric acid and
0.06ng/l for benzoic acid. This method has been applied to the
analysis of urine samples from the suspected of toluene abuser or
glue sniffer among secondary school students at Johor Bahru.
Abstract: This work proposes a recursive weighted ELS
algorithm for system identification by applying numerically robust
orthogonal Householder transformations. The properties of the
proposed algorithm show it obtains acceptable results in a noisy
environment: fast convergence and asymptotically unbiased
estimates. Comparative analysis with others robust methods well
known from literature are also presented.
Abstract: Swarm principles are increasingly being used to design controllers for the coordination of multi-robot systems or, in general, multi-agent systems. This paper proposes a two-dimensional Lagrangian swarm model that enables the planar agents, modeled as point masses, to swarm whilst effectively avoiding each other and obstacles in the environment. A novel method, based on an extended Lyapunov approach, is used to construct the model. Importantly, the Lyapunov method ensures a form of practical stability that guarantees an emergent behavior, namely, a cohesive and wellspaced swarm with a constant arrangement of individuals about the swarm centroid. Computer simulations illustrate this basic feature of collective behavior. As an application, we show how multiple planar mobile unicycle-like robots swarm to eventually form patterns in which their velocities and orientations stabilize.
Abstract: Female breast cancer is the second in frequency after cervical cancer. Surgery is the most common treatment for breast cancer, followed by chemotherapy as a treatment of choice. Although effective, it causes serious side effects. Controlled-release drug delivery is an alternative method to improve the efficacy and safety of the treatment. It can release the dosage of drug between the minimum effect concentration (MEC) and minimum toxic concentration (MTC) within tumor tissue and reduce the damage of normal tissue and the side effect. Because an in vivo experiment of this system can be time-consuming and labor-intensive, a mathematical model is desired to study the effects of important parameters before the experiments are performed. Here, we describe a 3D mathematical model to predict the release of doxorubicin from pluronic gel to treat human breast cancer. This model can, ultimately, be used to effectively design the in vivo experiments.
Abstract: The standard investigational method for obstructive
sleep apnea syndrome (OSAS) diagnosis is polysomnography (PSG),
which consists of a simultaneous, usually overnight recording of
multiple electro-physiological signals related to sleep and
wakefulness. This is an expensive, encumbering and not a readily
repeated protocol, and therefore there is need for simpler and easily
implemented screening and detection techniques. Identification of
apnea/hypopnea events in the screening recordings is the key factor
for the diagnosis of OSAS. The analysis of a solely single-lead
electrocardiographic (ECG) signal for OSAS diagnosis, which may
be done with portable devices, at patient-s home, is the challenge of
the last years. A novel artificial neural network (ANN) based
approach for feature extraction and automatic identification of
respiratory events in ECG signals is presented in this paper. A
nonlinear principal component analysis (NLPCA) method was
considered for feature extraction and support vector machine for
classification/recognition. An alternative representation of the
respiratory events by means of Kohonen type neural network is
discussed. Our prospective study was based on OSAS patients of the
Clinical Hospital of Pneumology from Iaşi, Romania, males and
females, as well as on non-OSAS investigated human subjects. Our
computed analysis includes a learning phase based on cross signal
PSG annotation.
Abstract: The techniques for estimating the adhesive and cohesive strength in high velocity oxy fuel (HVOF) thermal spray coatings have been discussed and compared. The development trend and the last investigation have been studied. We will focus on benefits and limitations of these methods in different process and materials.
Abstract: In this study, aeroelastic response and performance
analyses have been conducted for a 5MW-Class composite wind
turbine blade model. Advanced coupled numerical method based on
computational fluid dynamics (CFD) and computational flexible
multi-body dynamics (CFMBD) has been developed in order to
investigate aeroelastic responses and performance characteristics of
the rotating composite blade. Reynolds-Averaged Navier-Stokes
(RANS) equations with k-ω SST turbulence model were solved for
unsteady flow problems on the rotating turbine blade model. Also,
structural analyses considering rotating effect have been conducted
using the general nonlinear finite element method. A fully implicit
time marching scheme based on the Newmark direct integration
method is applied to solve the coupled aeroelastic governing equations
of the 3D turbine blade for fluid-structure interaction (FSI) problems.
Detailed dynamic responses and instantaneous velocity contour on the
blade surfaces which considering flow-separation effects were
presented to show the multi-physical phenomenon of the huge rotating
wind- turbine blade model.