Abstract: The understanding of the system level of biological behavior and phenomenon variously needs some elements such as gene sequence, protein structure, gene functions and metabolic pathways. Challenging problems are representing, learning and reasoning about these biochemical reactions, gene and protein structure, genotype and relation between the phenotype, and expression system on those interactions. The goal of our work is to understand the behaviors of the interactions networks and to model their evolution in time and in space. We propose in this study an ontological meta-model for the knowledge representation of the genetic regulatory networks. Ontology in artificial intelligence means the fundamental categories and relations that provide a framework for knowledge models. Domain ontology's are now commonly used to enable heterogeneous information resources, such as knowledge-based systems, to communicate with each other. The interest of our model is to represent the spatial, temporal and spatio-temporal knowledge. We validated our propositions in the genetic regulatory network of the Aarbidosis thaliana flower
Abstract: This paper presents a new method to detect high impedance faults in radial distribution systems. Magnitudes of third and fifth harmonic components of voltages and currents are used as a feature vector for fault discrimination. The proposed methodology uses a learning vector quantization (LVQ) neural network as a classifier for identifying high impedance arc-type faults. The network learns from the data obtained from simulation of a simple radial system under different fault and system conditions. Compared to a feed-forward neural network, a properly tuned LVQ network gives quicker response.
Abstract: With the explosive growth of data available on the
Internet, personalization of this information space become a
necessity. At present time with the rapid increasing popularity of the
WWW, Websites are playing a crucial role to convey knowledge and
information to the end users. Discovering hidden and meaningful
information about Web users usage patterns is critical to determine
effective marketing strategies to optimize the Web server usage for
accommodating future growth. The task of mining useful information
becomes more challenging when the Web traffic volume is enormous
and keeps on growing. In this paper, we propose a intelligent model
to discover and analyze useful knowledge from the available Web
log data.
Abstract: Presence of phytosterol compound in Durian seed
(Durio zibethinus) or known as King of fruits has been discovered
from screening work using reagent test. Further analysis work has
been carried out using mass spectrometer in order to support the
priliminary finding. Isolation and purification of the major
phytosterol has been carried out using an open column
chromatography. The separation was monitored using thin layer
chromatography (TLC). Major isolated compounds and purified
phytosterol were identified using mass spectrometer and nuclear
magnetic resonance (NMR). This novel finding could promote
utilization of durian seeds as a functional ingredient in food products
through production of standardized extract based on phytosterol
content.
Abstract: In the present work, we propose a new method for
solving the matrix equation AXB=F . The new method can
be considered as a generalized form of the well-known global full
orthogonalization method (Gl-FOM) for solving multiple linear
systems. Hence, the method will be called extended Gl-FOM (EGl-
FOM). For implementing EGl-FOM, generalized forms of block
Krylov subspace and global Arnoldi process are presented. Finally,
some numerical experiments are given to illustrate the efficiency of
our new method.
Abstract: Segmentation of Magnetic Resonance Imaging (MRI) images is the most challenging problems in medical imaging. This paper compares the performances of Seed-Based Region Growing (SBRG), Adaptive Network-Based Fuzzy Inference System (ANFIS) and Fuzzy c-Means (FCM) in brain abnormalities segmentation. Controlled experimental data is used, which designed in such a way that prior knowledge of the size of the abnormalities are known. This is done by cutting various sizes of abnormalities and pasting it onto normal brain tissues. The normal tissues or the background are divided into three different categories. The segmentation is done with fifty seven data of each category. The knowledge of the size of the abnormalities by the number of pixels are then compared with segmentation results of three techniques proposed. It was proven that the ANFIS returns the best segmentation performances in light abnormalities, whereas the SBRG on the other hand performed well in dark abnormalities segmentation.
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: We present a theory for optimal filtering of infinite sets of random signals. There are several new distinctive features of the proposed approach. First, we provide a single optimal filter for processing any signal from a given infinite signal set. Second, the filter is presented in the special form of a sum with p terms where each term is represented as a combination of three operations. Each operation is a special stage of the filtering aimed at facilitating the associated numerical work. Third, an iterative scheme is implemented into the filter structure to provide an improvement in the filter performance at each step of the scheme. The final step of the concerns signal compression and decompression. This step is based on the solution of a new rank-constrained matrix approximation problem. The solution to the matrix problem is described in this paper. A rigorous error analysis is given for the new filter.
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: The objective of this study is to determine the thermal comfort among worker at Malaysian automotive industry. One critical manual assembly workstation had been chosen as a subject for the study. The human subjects for the study constitute operators at Body Assembly Station of the factory. The environment examined was the Relative Humidity (%), Airflow (m/s), Air Temperature (°C) and Radiant Temperature (°C) of the surrounding workstation area. The environmental factors were measured using Babuc apparatus, which is capable to measure simultaneously those mentioned environmental factors. The time series data of fluctuating level of factors were plotted to identify the significant changes of factors. Then thermal comfort of the workers were assessed by using ISO Standard 7730 Thermal sensation scale by using Predicted Mean Vote (PMV). Further Predicted percentage dissatisfied (PPD) is used to estimate the thermal comfort satisfaction of the occupant. Finally the PPD versus PMV were plotted to present the thermal comfort scenario of workers involved in related workstation. The result of PMV at the related industry is between 1.8 and 2.3, where PPD at that building is between 60% to 84%. The survey result indicated that the temperature more influenced comfort to the occupants
Abstract: The overall objective of this paper is to retrieve soil
surfaces parameters namely, roughness and soil moisture related to
the dielectric constant by inverting the radar backscattered signal
from natural soil surfaces.
Because the classical description of roughness using statistical
parameters like the correlation length doesn't lead to satisfactory
results to predict radar backscattering, we used a multi-scale
roughness description using the wavelet transform and the Mallat
algorithm. In this description, the surface is considered as a
superposition of a finite number of one-dimensional Gaussian
processes each having a spatial scale. A second step in this study
consisted in adapting a direct model simulating radar backscattering
namely the small perturbation model to this multi-scale surface
description. We investigated the impact of this description on radar
backscattering through a sensitivity analysis of backscattering
coefficient to the multi-scale roughness parameters.
To perform the inversion of the small perturbation multi-scale
scattering model (MLS SPM) we used a multi-layer neural network
architecture trained by backpropagation learning rule. The inversion
leads to satisfactory results with a relative uncertainty of 8%.
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: 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 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: Skip cycle is a working strategy for spark ignition
engines, which allows changing the effective stroke of an engine
through skipping some of the four stroke cycles. This study proposes
a new mechanism to achieve the desired skip-cycle strategy for
internal combustion engines. The air and fuel leakage, which occurs
through the gas exchange, negatively affects the efficiency of the
engine at high speeds and loads. An absolute sealing is assured by
direct use of poppet valves, which are kept in fully closed position
during the skipped mode. All the components of the mechanism were
designed according to the real dimensions of the Anadolu Motor's
gasoline engine and modeled in 3D by means of CAD software. As
the mechanism operates in two modes, two dynamically equivalent
models are established to obtain the force and strength analysis for
critical components.
Abstract: In this paper, we propose APO, a new packet scheduling
scheme with Quality of Service (QoS) support for hybrid of
real and non-real time services in HSDPA networks. The APO
scheduling algorithm is based on the effective channel anticipation
model. In contrast to the traditional schemes, the proposed method is
implemented based on a cyclic non-work-conserving discipline.
Simulation results indicated that proposed scheme has good
capability to maximize the channel usage efficiency in compared to
another exist scheduling methods. Simulation results demonstrate the
effectiveness of the proposed algorithm.
Abstract: In many countries, digital city or ubiquitous city
(u-City) projects have been initiated to provide digitalized economic
environments to cities. Recently in Korea, Kangwon Province has
started the u-Kangwon project to boost local economy with digitalized
tourism services. We analyze the limitations of the ubiquitous IT
approach through the u-Kangwon case. We have found that travelers
are more interested in quality over speed in access of information. For
improved service quality, we are looking to develop an
IT-convergence service design framework (ISDF). The ISDF is based
on the service engineering technique and composed of three parts:
Service Design, Service Simulation, and the Service Platform.
Abstract: Solution of some practical problems is reduced to the
solution of the integro-differential equations. But for the numerical
solution of such equations basically quadrature methods or its
combination with multistep or one-step methods are used. The
quadrature methods basically is applied to calculation of the integral
participating in right hand side of integro-differential equations. As
this integral is of Volterra type, it is obvious that at replacement with
its integrated sum the upper limit of the sum depends on a current
point in which values of the integral are defined. Thus we receive the
integrated sum with variable boundary, to work with is hardly.
Therefore multistep method with the constant coefficients, which is
free from noted lack and gives the way for finding it-s coefficients is
present.