Abstract: The paper presents an applied study of a multivariate AR(p) process fitted to daily data from U.S. commodity futures markets with the use of Bayesian statistics. In the first part a detailed description of the methods used is given. In the second part two BVAR models are chosen one with assumption of lognormal, the second with normal distribution of prices conditioned on the parameters. For a comparison two simple benchmark models are chosen that are commonly used in todays Financial Mathematics. The article compares the quality of predictions of all the models, tries to find an adequate rate of forgetting of information and questions the validity of Efficient Market Hypothesis in the semi-strong form.
Abstract: Autoregressive Moving average (ARMA) is a parametric based method of signal representation. It is suitable for problems in which the signal can be modeled by explicit known source functions with a few adjustable parameters. Various methods have been suggested for the coefficients determination among which are Prony, Pade, Autocorrelation, Covariance and most recently, the use of Artificial Neural Network technique. In this paper, the method of using Artificial Neural network (ANN) technique is compared with some known and widely acceptable techniques. The comparisons is entirely based on the value of the coefficients obtained. Result obtained shows that the use of ANN also gives accurate in computing the coefficients of an ARMA system.
Abstract: A direct downconversion receiver implemented in 0.13 μm 1P8M process is presented. The circuit is formed by a single-end LNA, an active balun for conversion into balanced mode, a quadrature double-balanced passive switch mixer and a quadrature voltage-controlled oscillator. The receiver operates in the 2.4 GHz ISM band and complies with IEEE 802.15.4 (ZigBee) specifications. The circuit exhibits a very low noise figure of only 2.27 dB and dissipates only 14.6 mW with a 1.2 V supply voltage and is hence suitable for low-power applications.
Abstract: In this study, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive output recurrent cerebellar model articulation control (AORCMAC) and H∞ control technique is proposed for wheeled inverted pendulums (WIPs) real-time control with exact system dynamics unknown. Moreover, a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. The experimental results indicate that the WIPs can stand upright stably when using the proposed RIBTC.
Abstract: Polyurethane foam (PUF) is formed by a chemical
reaction of polyol and isocyanate. The aim is to understand the
impact of Silicone on synthesizing polyurethane in differentiate
volume of molding. The method used was one step process, which is
simultaneously caried out a blending polyol (petroleum polyol and
soybean polyol), a TDI (2,4):MDI (4,4-) (80:20), a distilled water,
and a silicone. The properties of the material were measured via a
number of parameters, which are polymer density, compressive
strength, and cellular structures. It is found that density of
polyurethane using silicone with volume of molding either 250 ml or
500 ml is lower than without using silicone.
Abstract: A number of mass spectrometry applications are already available as web-based and windows-based systems to calculate isotope pattern and to display the mass spectrum based on the specific molecular formula besides providing necessary information. These applications were evaluated and compared with our new alternative application called Theoretical Isotope Generator (TIG) in terms of its functionality and features provided to prove this new application is working better and performing well. TIG provides extra features than others, complete with several functionality such as drawing, normalizing and zooming the generated graph that convey with the molecular information in a number of formats by providing the details of the calculation and molecules. Thus, any chemist, students, lecturers and researchers from anywhere could use TIG to gain related information on molecules and their relative intensity.
Abstract: A liquid curved jet has many applications in different
industrial and engineering processes, such as the prilling process
for generating small spherical pellets (fertilizer or magnesium). The
liquids used are usually molten and contain small quantities of
polymers and therefore can be modelled as non-Newtonian liquids. In
this paper, we model the viscoelastic liquid jet by using the Oldroyd-
B model. An asymptotic analysis has been used to simplify the
governing equations. Furthermore, the trajectory and a linear temporal
stability in the presence of gravity and rotation have been determined.
Abstract: In this study, the two dimensional heat conduction
problem for the dry friction clutch disc is modeled mathematically
analysis and is solved numerically using finite element method, to
determine the temperature field when band contacts occurs between
the rubbing surfaces during the operation of an automotive clutch.
Temperature calculation have been made for contact area of different
band width and the results obtained compared with these attained
when complete contact occurs. Furthermore, the effects of slipping
time and sliding velocity function are investigated as well. Both
single and repeated engagements made at regular interval are
considered.
Abstract: This study aims at investigating the empirical
relationships between risk preference, internet preference, and
internet knowledge which are known as user characteristics, in
addition to perceived risk of the customers on the internet purchase
intention. In order to test the relationships between the variables of
model 174, a questionnaire was collected from the students with
previous online experience. For the purpose of data analysis,
confirmatory factor analysis (CFA) and structural equation model
(SEM) was used.
Test results show that the perceived risk affects the internet
purchase intention, and increase or decrease of perceived risk
influences the purchase intention when the customer does the internet
shopping. Other factors such as internet preference, knowledge of the
internet, and risk preference affect the internet purchase intention.
Abstract: In this paper, we propose a novel spatiotemporal fuzzy
based algorithm for noise filtering of image sequences. Our proposed algorithm uses adaptive weights based on a triangular membership
functions. In this algorithm median filter is used to suppress noise.
Experimental results show when the images are corrupted by highdensity
Salt and Pepper noise, our fuzzy based algorithm for noise filtering of image sequences, are much more effective in suppressing
noise and preserving edges than the previously reported algorithms such as [1-7]. Indeed, assigned weights to noisy pixels are very
adaptive so that they well make use of correlation of pixels. On the other hand, the motion estimation methods are erroneous and in highdensity noise they may degrade the filter performance. Therefore, our
proposed fuzzy algorithm doesn-t need any estimation of motion trajectory. The proposed algorithm admissibly removes noise without having any knowledge of Salt and Pepper noise density.
Abstract: Psoriasis is a widespread skin disease affecting up to 2% population with plaque psoriasis accounting to about 80%. It can be identified as a red lesion and for the higher severity the lesion is usually covered with rough scale. Psoriasis Area Severity Index (PASI) scoring is the gold standard method for measuring psoriasis severity. Scaliness is one of PASI parameter that needs to be quantified in PASI scoring. Surface roughness of lesion can be used as a scaliness feature, since existing scale on lesion surface makes the lesion rougher. The dermatologist usually assesses the severity through their tactile sense, therefore direct contact between doctor and patient is required. The problem is the doctor may not assess the lesion objectively. In this paper, a digital image analysis technique is developed to objectively determine the scaliness of the psoriasis lesion and provide the PASI scaliness score. Psoriasis lesion is modelled by a rough surface. The rough surface is created by superimposing a smooth average (curve) surface with a triangular waveform. For roughness determination, a polynomial surface fitting is used to estimate average surface followed by a subtraction between rough and average surface to give elevation surface (surface deviations). Roughness index is calculated by using average roughness equation to the height map matrix. The roughness algorithm has been tested to 444 lesion models. From roughness validation result, only 6 models can not be accepted (percentage error is greater than 10%). These errors occur due the scanned image quality. Roughness algorithm is validated for roughness measurement on abrasive papers at flat surface. The Pearson-s correlation coefficient of grade value (G) of abrasive paper and Ra is -0.9488, its shows there is a strong relation between G and Ra. The algorithm needs to be improved by surface filtering, especially to overcome a problem with noisy data.
Abstract: To compute dynamic characteristics of nonlinear viscoelastic springs with elastic structures having huge degree-of-freedom, Yamaguchi proposed a new fast numerical method using finite element method [1]-[2]. In this method, restoring forces of the springs are expressed using power series of their elongation. In the expression, nonlinear hysteresis damping is introduced. In this expression, nonlinear complex spring constants are introduced. Finite element for the nonlinear spring having complex coefficients is expressed and is connected to the elastic structures modeled by linear solid finite element. Further, to save computational time, the discrete equations in physical coordinate are transformed into the nonlinear ordinary coupled equations using normal coordinate corresponding to linear natural modes. In this report, the proposed method is applied to simulation for impact responses of a viscoelastic shock absorber with an elastic structure (an S-shaped structure) by colliding with a concentrated mass. The concentrated mass has initial velocities and collides with the shock absorber. Accelerations of the elastic structure and the concentrated mass are measured using Levitation Mass Method proposed by Fujii [3]. The calculated accelerations from the proposed FEM, corresponds to the experimental ones. Moreover, using this method, we also investigate dynamic errors of the S-shaped force transducer due to elastic mode in the S-shaped structure.
Abstract: This paper focuses on the calibration problem of a
multi-view shooting system designed for the production of 3D
content for auto-stereoscopic visualization. The considered multiview
camera is characterized by coplanar and decentered image
sensors regarding to the corresponding optical axis. Based on the
Faugéras and Toscani-s calibration approach, a calibration method is
herein proposed for the case of multi-view camera with parallel and
decentered image sensors. At first, the geometrical model of the
shooting system is recalled and some industrial prototypes with some
shooting simulations are presented. Next, the development of the
proposed calibration method is detailed. Finally, some simulation
results are presented before ending with some conclusions about this
work.
Abstract: A portable sensor for the analysis of phosphate in
aqueous samples has been developed. The sensor incorporates
microfluidic technology, colorimetric detection, and wireless
communications into a compact and rugged portable device. The
detection method used is the molybdenum yellow method, in which a
phosphate-containing sample is mixed with a reagent containing
ammonium metavanadate and ammonium molybdate in an acidic
medium. A yellow-coloured compound is generated and the
absorption of this compound is measured using a light emitting diode
(LED) light source and a photodiode detector. The absorption is
directly proportional to the phosphate concentration in the original
sample. In this paper we describe the application of this phosphate
sensor to the analysis of wastewater at a municipal wastewater
treatment plant in Co. Kildare, Ireland.
Abstract: This paper presents the results of preliminary
assessment of water quality along the coastal areas in the vicinity of
Left Bank Outfall Drainage (LBOD) and Tidal Link Drain (TLD) in
Sindh province after the cyclone 2A occurred in 1999. The water
samples were collected from various RDs of Tidal Link Drain and
lakes during September 2001 to April 2002 and were analysed for
salinity, nitrite, phosphate, ammonia, silicate and suspended material
in water. The results of the study showed considerable variations in
water quality depending upon the location along the coast in the
vicinity of LBOD and RDs. The salinity ranged between 4.39–65.25
ppt in Tidal Link Drain samples whereas 2.4–38.05 ppt in samples
collected from lakes. The values of suspended material at various
RDs of Tidal Link Drain ranged between 56.6–2134 ppm and at the
lakes between 68–297 ppm. The data of continuous monitoring at
RD–93 showed the range of PO4 (8.6–25.2 μg/l), SiO3 (554.96–1462
μg/l), NO2 (0.557.2–25.2 μg/l) and NH3 (9.38–23.62 μg/l). The
concentration of nutrients in water samples collected from different
RDs was found in the range of PO4 (10.85 to 11.47 μg/l), SiO3 (1624
to 2635.08 μg/l), NO2 (20.38 to 44.8 μg/l) and NH3 (24.08 to 26.6
μg/l). Sindh coastal areas which situated at the north-western
boundary the Arabian Sea are highly vulnerable to flood damages
due to flash floods during SW monsoon or impact of sea level rise
and storm surges coupled with cyclones passing through Arabian Sea
along Pakistan coast. It is hoped that the obtained data in this study
would act as a database for future investigations and monitoring of
LBOD and Tidal Link Drain coastal waters.
Abstract: The aim of this study was to synthesize the single
walled carbon nanotubes (SWCNTs) and determine their hydrogen
storage capacities. SWCNTs were firstly synthesized by chemical
vapor deposition (CVD) of acetylene (C2H2) on a magnesium oxide
(MgO) powder impregnated with an iron nitrate (Fe(NO3)3·9H2O)
solution. The synthesis parameters were selected as: the synthesis
temperature of 800°C, the iron content in the precursor of 5% and the
synthesis time of 30 min. Purification process of SWCNTs was
fulfilled by microwave digestion at three different temperatures (120,
150 and 200 °C), three different acid concentrations (0.5, 1 and 1.5
M) and for three different time intervals (15, 30 and 60 min). Nitric
acid (HNO3) was used in the removal of the metal catalysts. The
hydrogen storage capacities of the purified materials were measured
using volumetric method at the liquid nitrogen temperature and gas
pressure up to 100 bar. The effects of the purification conditions such
as temperature, time and acid concentration on hydrogen adsorption
were investigated.
Abstract: An experiment was performed with a 24.5 MeV 14N
beam on a 12C target in the cyclotron DC-60 located in Astana,
Kazakhstan, to study the elastic scattering of 14N on 12C; the
scattering was also analyzed at different energies for tracking the
phenomenon of remarkable structure at large angles. Its aims were to
extend the measurements to very large angles, and attempt to
uniquely identify the elastic scattering potential. Good agreement
between the theoretical and experimental data has been obtained with
suitable optical potential parameters. Optical model calculations with
l -dependent imaginary potentials were also applied to the data and
relatively good agreement was found.
Abstract: all of religions free towards society in Kazakhstan. Considering that Islam is more widespread religion in the region, Islamic industry is developing sector of Economy. There are some new sectors of Halal (Islamic) industry, which have importance for state developing on the whole. One of the youngest sectors of Halal industry is Islamic tourism, which became an object of disputes and led to dilemma, such as Islamic tourism is a result of a Religious revival and Islamic tourism is a new trend of Tourism. The paper was written under the research project “Islam in modern Kazakhstan: the nature and outcome of the religious revival".
Abstract: Knowledge sharing enables the information or
knowledge to be transmitted from one source to another. This paper
demonstrates the needs of having the online book catalogue which
can be used to facilitate disseminating information on textbook used
in the university. This project is aimed to give access to the students
and lecturers to the list of books in the bookstore and at the same
time to allow book reviewing without having to visit the bookstore
physically. Research is carried out according to the boundaries which
accounts to current process of new book purchasing, current system
used by the bookstore and current process the lecturers go through
for reviewing textbooks. The questionnaire is used to gather the
requirements and it is distributed to 100 students and 40 lecturers.
This project has enabled the improvement of a manual process to be
carried out automatically, through a web based platform. It is shown
based on the user acceptance survey carried out that target groups
found that this web service is feasible to be implemented in
Universiti Teknologi PETRONAS (UTP), and they have shown
positive signs of interest in utilizing it in the future.
Abstract: This paper presents a novel methodology for Maximum Power Point Tracking (MPPT) of a grid-connected 20 kW Photovoltaic (PV) system using neuro-fuzzy network. The proposed method predicts the reference PV voltage guarantying optimal power transfer between the PV generator and the main utility grid. The neuro-fuzzy network is composed of a fuzzy rule-based classifier and three Radial Basis Function Neural Networks (RBFNN). Inputs of the network (irradiance and temperature) are classified before they are fed into the appropriated RBFNN for either training or estimation process while the output is the reference voltage. The main advantage of the proposed methodology, comparing to a conventional single neural network-based approach, is the distinct generalization ability regarding to the nonlinear and dynamic behavior of a PV generator. In fact, the neuro-fuzzy network is a neural network based multi-model machine learning that defines a set of local models emulating the complex and non-linear behavior of a PV generator under a wide range of operating conditions. Simulation results under several rapid irradiance variations proved that the proposed MPPT method fulfilled the highest efficiency comparing to a conventional single neural network.