Abstract: Design of an observer based controller for a class of
fractional order systems has been done. Fractional order mathematics
is used to express the system and the proposed observer. Fractional
order Lyapunov theorem is used to derive the closed-loop asymptotic
stability. The gains of the observer and observer based controller are
derived systematically using the linear matrix inequality approach.
Finally, the simulation results demonstrate validity and effectiveness
of the proposed observer based controller.
Abstract: The main purpose of this research aimed to create tactile texture designed media for the blind used for extra learning outside classrooms in order to enhance imagination of the blind about Himmapan creatures, furthermore, the main objective of the research focused on improving the visual disabled perception to be equal to normal people. The target group of the research is blinded students studying in The Bangkok school for the blind between grade 4-6 in the second semester of 2011 who are able to read the braille language. The research methodology consisted of the field study and the documentary study related to the blind, tactile texture designed media and Himmapan creatures. 10 pictures of tactile texture designed media were created in the designing process which began after the analysis had conducted based the primary and secondary data. The works had presented to experts in the visual disabled field who evaluated the works. After approval, the works used as prototype to teach the blind. KeywordsBlind, Himmapan Creatures, Tactile Texture.
Abstract: This paper draws a methodological framework adopted within an internal Telecomitalia project aimed to identify, on a user centred base, the potential interest towards a technological scenario aimed to extend on a personal bubble the typical communication and media fruition home environment. The problem is that involving user in the early stage of the development of such disruptive technology scenario asking users opinions on something that users actually do not manage even in a rough manner could lead to wrong or distorted results. For that reason we chose an approach that indirectly aim to understand users hidden needs in order to obtain a meaningful picture of the possible interest for a technological proposition non yet easily understandable.
Abstract: Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.
Abstract: In this paper we propose a Particle Swarm heuristic
optimized Multi-Antenna (MA) system. Efficient MA systems
detection is performed using a robust stochastic evolutionary
computation algorithm based on movement and intelligence of
swarms. This iterative particle swarm optimized (PSO) detector
significantly reduces the computational complexity of conventional
Maximum Likelihood (ML) detection technique. The simulation
results achieved with this proposed MA-PSO detection algorithm
show near optimal performance when compared with ML-MA
receiver. The performance of proposed detector is convincingly
better for higher order modulation schemes and large number of
antennas where conventional ML detector becomes non-practical.
Abstract: Simulation model is an easy way to build up models
to represent real life scenarios, to identify bottlenecks and to enhance
system performance. Using a valid simulation model may give
several advantages in creating better manufacturing design in order to
improve the system performances. This paper presents result of
implementing a simulation model to design hard disk drive
manufacturing process by applying line balancing to improve both
productivity and quality of hard disk drive process. The line balance
efficiency showed 86% decrease in work in process, output was
increased by an average of 80%, average time in the system was
decreased 86% and waiting time was decreased 90%.
Abstract: We present new finite element methods for Helmholtz and Maxwell equations on general three-dimensional polyhedral meshes, based on domain decomposition with boundary elements on the surfaces of the polyhedral volume elements. The methods use the lowest-order polynomial spaces and produce sparse, symmetric linear systems despite the use of boundary elements. Moreover, piecewise constant coefficients are admissible. The resulting approximation on the element surfaces can be extended throughout the domain via representation formulas. Numerical experiments confirm that the convergence behavior on tetrahedral meshes is comparable to that of standard finite element methods, and equally good performance is attained on more general meshes.
Abstract: In this study we focus on improvement performance
of a cue based Motor Imagery Brain Computer Interface (BCI). For
this purpose, data fusion approach is used on results of different
classifiers to make the best decision. At first step Distinction
Sensitive Learning Vector Quantization method is used as a feature
selection method to determine most informative frequencies in
recorded signals and its performance is evaluated by frequency
search method. Then informative features are extracted by packet
wavelet transform. In next step 5 different types of classification
methods are applied. The methodologies are tested on BCI
Competition II dataset III, the best obtained accuracy is 85% and the
best kappa value is 0.8. At final step ordered weighted averaging
(OWA) method is used to provide a proper aggregation classifiers
outputs. Using OWA enhanced system accuracy to 95% and kappa
value to 0.9. Applying OWA just uses 50 milliseconds for
performing calculation.
Abstract: Sugarcane bagasses are one of the most extensively used agricultural residues. Using acid hydrolysis and fermentation, conversion of sugarcane bagasses to lactic acid was technically and economically feasible. This research was concerned with the solubility of lignin in ammonium hydroxide, acid hydrolysis and lactic acid fermentation by Lactococcus lactis, Lactobacillus delbrueckii, Lactobacillus plantarum, and Lactobacillus casei. The lignin extraction results for different ammonium hydroxide concentrations showed that 10 % (v/v) NH4OH was favorable to lignin dissolution. Acid hydrolysis can be enhanced with increasing acid concentration and reaction temperature. The optimum glucose and xylose concentrations occurred at 121 ○C for 1 hour hydrolysis time in 10% sulphuric acid solution were 32 and 11 g/l, respectively. In order to investigate the significance of medium composition on lactic acid production, experiments were undertaken whereby a culture of Lactococcus lactis was grown under various glucose, peptone, yeast extract and xylose concentrations. The optimum medium was composed of 5 g/l glucose, 2.5 g/l xylose, 10 g/l peptone and 5 g/l yeast extract. Lactococcus lactis represents the most efficient for lactic acid production amongst those considered. The lactic acid fermentation by Lactococcus lactis after 72 hours gave the highest yield of 1.4 (g lactic acid per g reducing sugar).
Abstract: This study empirically examines the long run equilibrium relationship between South Africa’s exports and imports using quarterly data from 1985 to 2012. The theoretical framework used for the study is based on Johansen’s Maximum Likelihood cointegration technique which tests for both the existence and number of cointegration vectors that exists. The study finds that both the series are integrated of order one and are cointegrated. A statistically significant cointegrating relationship is found to exist between exports and imports. The study models this unique linear and lagged relationship using a Vector Error Correction Model (VECM). The findings of the study confirm the existence of a long run equilibrium relationship between exports and imports.
Abstract: Change in impedance of an encircling coil is obtained
in the present paper for the case where the electric conductivity and
magnetic permeability of a metal cylindrical tube depend on the
radial coordinate. The system of equations for the vector potential is
solved by means of the Fourier cosine transform. The solution is
expressed in terms of improper integral containing modified Bessel
functions of complex order.
Abstract: This article presents the development of a neural
network cognitive model for the classification and detection of
different frequency signals. The basic structure of the implemented
neural network was inspired on the perception process that humans
generally make in order to visually distinguish between high and low
frequency signals. It is based on the dynamic neural network concept,
with delays. A special two-layer feedforward neural net structure was
successfully implemented, trained and validated, to achieve
minimum target error. Training confirmed that this neural net
structure descents and converges to a human perception classification
solution, even when far away from the target.
Abstract: In order to provide accurate heart rate variability
indices of sympathetic and parasympathetic activity, the low
frequency and high frequency components of an RR heart rate signal
must be adequately separated. This is not always possible by just
applying spectral analysis, as power from the high and low frequency
components often leak into their adjacent bands. Furthermore,
without the respiratory spectra it is not obvious that the low
frequency component is not another respiratory component, which
can appear in the lower band. This paper describes an adaptive filter,
which aids the separation of the low frequency sympathetic and high
frequency parasympathetic components from an ECG R-R interval
signal, enabling the attainment of more accurate heart rate variability
measures. The algorithm is applied to simulated signals and heart rate
and respiratory signals acquired from an ambulatory monitor
incorporating single lead ECG and inductive plethysmography
sensors embedded in a garment. The results show an improvement
over standard heart rate variability spectral measurements.
Abstract: In data mining, the association rules are used to find
for the associations between the different items of the transactions
database. As the data collected and stored, rules of value can be found
through association rules, which can be applied to help managers
execute marketing strategies and establish sound market frameworks.
This paper aims to use Fuzzy Frequent Pattern growth (FFP-growth)
to derive from fuzzy association rules. At first, we apply fuzzy
partition methods and decide a membership function of quantitative
value for each transaction item. Next, we implement FFP-growth
to deal with the process of data mining. In addition, in order to
understand the impact of Apriori algorithm and FFP-growth algorithm
on the execution time and the number of generated association
rules, the experiment will be performed by using different sizes of
databases and thresholds. Lastly, the experiment results show FFPgrowth
algorithm is more efficient than other existing methods.
Abstract: This paper describes a 2.4 GHz passive switch mixer
and a 5/2.5 GHz voltage-controlled negative Gm oscillator (VCO)
with an inversion-mode MOS varactor. Both circuits are implemented
using a 1P8M 0.13 μm process. The switch mixer has an input
referred 1 dB compression point of -3.89 dBm and a conversion
gain of -0.96 dB when the local oscillator power is +2.5 dBm.
The VCO consumes only 1.75 mW, while drawing 1.45 mA from a
1.2 V supply voltage. In order to reduce the passives size, the VCO
natural oscillation frequency is 5 GHz. A clocked CMOS divideby-
two circuit is used for frequency division and quadrature phase
generation. The VCO has a -109 dBc/Hz phase noise at 1 MHz
frequency offset and a 2.35-2.5 GHz tuning range (after the frequency
division), thus complying with ZigBee requirements.
Abstract: Anodizing is an electrochemical process that converts the metal surface into a decorative, durable, corrosion-resistant, anodic oxide finish. Aluminum is ideally suited to anodizing, although other nonferrous metals, such as magnesium and titanium, also can be anodized. The anodic oxide structure originates from the aluminum substrate and is composed entirely of aluminum oxide. This aluminum oxide is not applied to the surface like paint or plating, but is fully integrated with the underlying aluminum substrate, so cannot chip or peel. It has a highly ordered, porous structure that allows for secondary processes such as coloring and sealing. In this experimental paper, we focus on a reliable method for fabricating nanoporous alumina with high regularity. Starting from study of nanostructure materials synthesize methods. After that, porous alumina fabricate in the laboratory by anodization of aluminum oxide. Hard anodization processes are employed to fabricate the nanoporous alumina using 0.3M oxalic acid and 90, 120 and 140 anodized voltages. The nanoporous templates were characterized by SEM and FFT. The nanoporous templates using 140 voltages have high ordered. The pore formation, influence of the experimental conditions on the pore formation, the structural characteristics of the pore and the oxide chemical reactions involved in the pore growth are discuss.
Abstract: This work presents a recursive identification algorithm. This algorithm relates to the identification of closed loop system with Variable Structure Controller. The approach suggested includes two stages. In the first stage a genetic algorithm is used to obtain the parameters of switching function which gives a control signal rich in commutations (i.e. a control signal whose spectral characteristics are closest possible to those of a white noise signal). The second stage consists in the identification of the system parameters by the instrumental variable method and using the optimal switching function parameters obtained with the genetic algorithm. In order to test the validity of this algorithm a simulation example is presented.
Abstract: Medical compression bandages are widely used in the
treatment of chronic venous disorder. In order to design effective
compression bandages, researchers have attempted to describe the
interface pressure applied by multi-layer bandages using mathematical
models. This paper reports on the work carried out to
compare and validate the mathematical models used to describe the
interface pressure applied by multi-layer bandages. Both analytical
and experimental results showed that using simple multiplication
of a number of bandage layers with the pressure applied by one
layer of bandage or ignoring the increase in the limb radius due to
former layers of bandage will result in overestimating the pressure.
Experimental results showed that the mathematical models, which
take into consideration the increase in the limb radius due to former
bandage layers, are more accurate than the one which does not.
Abstract: In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.
Abstract: Within dental-guided surgery, there has been a lack
of analytical methods for optimizing the treatment of the
rehabilitation concepts regarding geometrical variation. The purpose
of this study is to find the source of the greatest geometrical variation
contributor and sensitivity contributor with the help of virtual
variation simulation of a dental drill- and implant-guided surgery
process using a methodical approach. It is believed that lower
geometrical variation will lead to better patient security and higher
quality of dental drill- and implant-guided surgeries. It was found
that the origin of the greatest contributor to the most variation, and
hence where the foci should be set, in order to minimize geometrical
variation was in the assembly category (surgery). This was also the
category that was the most sensitive for geometrical variation.