Abstract: In the present study, the effects of ultrasound as
emerging technology were investigated on germination stimulation,
amount of alpha-amylase activity on dry barley seeds before steeping
stage of malting process. All experiments were carried out at 20 KHz
on the ultrasonic generator in 3 different ultrasonic intensities (20, 60
and 100% setting from total power of device) and time (5, 10 and 15
min) at constant temperature (30C). For determining the effects of
these parameters on enzyme the Fuwa method assay based on the
decreased staining value of blue starch–iodine complexes employed
for measurement an activity. The results of these assays were
analyzed by Qualitek4 software using the Taguchi statistical method
to evaluate the factor-s effects on enzyme activity. It has been found
that when malting barley is irradiated with an ultrasonic power, a
stimulating effect occurs as to the enzyme activity.
Abstract: IETF RFC 2002 originally introduced the wireless
Mobile-IP protocol to support portable IP addresses for mobile
devices that often change their network access points to the Internet.
The inefficiency of this protocol mainly within the handoff
management produces large end-to-end packet delays, during
registration process, and further degrades the system efficiency due to
packet losses between subnets. The criterion to initiate a simple and
fast full-duplex connection between the home agent and foreign
agent, to reduce the roaming duration, is a very important issue to be
considered by a work in this paper. State-transition Petri-Nets of the
modeling scenario-based CIA: communication inter-agents procedure
as an extension to the basic Mobile-IP registration process was
designed and manipulated. The heuristic of configuration file during
practical Setup session for registration parameters, on Cisco platform
Router-1760 using IOS 12.3 (15)T is created. Finally, stand-alone
performance simulations results from Simulink Matlab, within each
subnet and also between subnets, are illustrated for reporting better
end-to-end packet delays. Results verified the effectiveness of our
Mathcad analytical manipulation and experimental implementation. It
showed lower values of end-to-end packet delay for Mobile-IP using
CIA procedure. Furthermore, it reported packets flow between
subnets to improve packet losses between subnets.
Abstract: Three reactor types were explored and successfully
used for pigment production by Monascus: shake flasks, and shaken
and stirred miniaturized reactors. Also, the use of dielectric
spectroscopy for the on-line measurement of biomass levels was
explored. Shake flasks gave good pigment yields, but scale up is
difficult, and they cannot be automated. Shaken bioreactors were less
successful with pigment production than stirred reactors.
Experiments with different impeller speeds in different volumes of
liquid in the reactor confirmed that this is most likely due oxygen
availability. The availability of oxygen appeared to affect biomass
levels less than pigment production; red pigment production in
particular needed very high oxygen levels. Dielectric spectroscopy
was effectively used to continuously measure biomass levels during
the submerged fungal fermentation in the shaken and stirred
miniaturized bioreactors, despite the presence of the solid substrate
particles. Also, the capacitance signal gave useful information about
the viability of the cells in the culture.
Abstract: Information Retrieval has the objective of studying
models and the realization of systems allowing a user to find the
relevant documents adapted to his need of information. The
information search is a problem which remains difficult because the
difficulty in the representing and to treat the natural languages such
as polysemia. Intentional Structures promise to be a new paradigm to
extend the existing documents structures and to enhance the different
phases of documents process such as creation, editing, search and
retrieval. The intention recognition of the author-s of texts can reduce
the largeness of this problem. In this article, we present intentions
recognition system is based on a semi-automatic method of
extraction the intentional information starting from a corpus of text.
This system is also able to update the ontology of intentions for the
enrichment of the knowledge base containing all possible intentions
of a domain. This approach uses the construction of a semi-formal
ontology which considered as the conceptualization of the intentional
information contained in a text. An experiments on scientific
publications in the field of computer science was considered to
validate this approach.
Abstract: In this study, the effects of biogas fuels on the performance of an annular micro gas turbine (MGT) were assessed experimentally and numerically. In the experiments, the proposed MGT system was operated successfully under each test condition; minimum composition to the fuel with the biogas was roughly 50% CH4 with 50% CO2. The power output was around 170W at 85,000 RPM as 90% CH4 with 10% CO2 was used and 70W at 65,000 RPM as 70% CH4 with 30% CO2 was used. When a critical limit of 60% CH4 was reached, the power output was extremely low. Furthermore, the theoretical Brayton cycle efficiency and electric efficiency of the MGT were calculated as 23% and 10%, respectively. Following the experiments, the measured data helped us identify the parameters of dynamic model in numerical simulation. Additionally, a numerical analysis of re-designed combustion chamber showed that the performance of MGT could be improved by raising the temperature at turbine inlet. This study presents a novel distributed power supply system that can utilize renewable biogas. The completed micro biogas power supply system is small, low cost, easy to maintain and suited to household use.
Abstract: Image target detection and tracking methods based on
target information such as intensity, shape model, histogram and
target dynamics have been proven to be robust to target model
variations and background clutters as shown by recent researches.
However, no definitive answer has been given to occluded target by
counter measure or limited field of view(FOV). In this paper, we
will present a novel tracking method using filtering and computational
geometry. This paper has two central goals: 1) to deal with vulnerable
target measurements; and 2) to maintain target tracking out of FOV
using non-target-originated information. The experimental results,
obtained with airborne images, show a robust tracking ability with
respect to the existing approaches. In exploring the questions of target
tracking, this paper will be limited to consideration of airborne image.
Abstract: In recent years with the rapid development of Internet and the Web, more and more web applications have been deployed in many fields and organizations such as finance, military, and government. Together with that, hackers have found more subtle ways to attack web applications. According to international statistics, SQL Injection is one of the most popular vulnerabilities of web applications. The consequences of this type of attacks are quite dangerous, such as sensitive information could be stolen or authentication systems might be by-passed. To mitigate the situation, several techniques have been adopted. In this research, a security solution is proposed using Artificial Neural Network to protect web applications against this type of attacks. The solution has been experimented on sample datasets and has given promising result. The solution has also been developed in a prototypic web application firewall called ANNbWAF.
Abstract: Cognitive Science appeared about 40 years ago,
subsequent to the challenge of the Artificial Intelligence, as common
territory for several scientific disciplines such as: IT, mathematics,
psychology, neurology, philosophy, sociology, and linguistics. The
new born science was justified by the complexity of the problems
related to the human knowledge on one hand, and on the other by the
fact that none of the above mentioned sciences could explain alone
the mental phenomena. Based on the data supplied by the
experimental sciences such as psychology or neurology, models of
the human mind operation are built in the cognition science. These
models are implemented in computer programs and/or electronic
circuits (specific to the artificial intelligence) – cognitive systems –
whose competences and performances are compared to the human
ones, leading to the psychology and neurology data reinterpretation,
respectively to the construction of new models. During these
processes if psychology provides the experimental basis, philosophy
and mathematics provides the abstraction level utterly necessary for
the intermission of the mentioned sciences.
The ongoing general problematic of the cognitive approach
provides two important types of approach: the computational one,
starting from the idea that the mental phenomenon can be reduced to
1 and 0 type calculus operations, and the connection one that
considers the thinking products as being a result of the interaction
between all the composing (included) systems. In the field of
psychology measurements in the computational register use classical
inquiries and psychometrical tests, generally based on calculus
methods. Deeming things from both sides that are representing the
cognitive science, we can notice a gap in psychological product
measurement possibilities, regarded from the connectionist
perspective, that requires the unitary understanding of the quality –
quantity whole. In such approach measurement by calculus proves to
be inefficient. Our researches, deployed for longer than 20 years,
lead to the conclusion that measuring by forms properly fits to the
connectionism laws and principles.
Abstract: Robots- visual perception is a field that is gaining
increasing attention from researchers. This is partly due to emerging
trends in the commercial availability of 3D scanning systems or
devices that produce a high information accuracy level for a variety of
applications. In the history of mining, the mortality rate of mine workers
has been alarming and robots exhibit a great deal of potentials to
tackle safety issues in mines. However, an effective vision system
is crucial to safe autonomous navigation in underground terrains.
This work investigates robots- perception in underground terrains
(mines and tunnels) using statistical region merging (SRM) model.
SRM reconstructs the main structural components of an imagery
by a simple but effective statistical analysis. An investigation is
conducted on different regions of the mine, such as the shaft, stope
and gallery, using publicly available mine frames, with a stream of
locally captured mine images. An investigation is also conducted on a
stream of underground tunnel image frames, using the XBOX Kinect
3D sensors. The Kinect sensors produce streams of red, green and
blue (RGB) and depth images of 640 x 480 resolution at 30 frames per
second. Integrating the depth information to drivability gives a strong
cue to the analysis, which detects 3D results augmenting drivable and
non-drivable regions in 2D. The results of the 2D and 3D experiment
with different terrains, mines and tunnels, together with the qualitative
and quantitative evaluation, reveal that a good drivable region can be
detected in dynamic underground terrains.
Abstract: This work has been carried out in order to provide an understanding of the physical behaviors of the flow variation of pressure and temperature in a vortex tube. A computational fluid dynamics model is used to predict the flow fields and the associated temperature separation within a Ranque–Hilsch vortex tube. The CFD model is a steady axisymmetric model (with swirl) that utilizes the standard k-ε turbulence model. The second–order numerical schemes, was used to carry out all the computations. Vortex tube with a circumferential inlet stream and an axial (cold) outlet stream and a circumferential (hot) outlet stream was considered. Performance curves (temperature separation versus cold outlet mass fraction) were obtained for a specific vortex tube with a given inlet mass flow rate. Simulations have been carried out for varying amounts of cold outlet mass flow rates. The model results have a good agreement with experimental data.
Abstract: Instead of traditional (nominal) classification we investigate
the subject of ordinal classification or ranking. An enhanced
method based on an ensemble of Support Vector Machines (SVM-s)
is proposed. Each binary classifier is trained with specific weights
for each object in the training data set. Experiments on benchmark
datasets and synthetic data indicate that the performance of our
approach is comparable to state of the art kernel methods for
ordinal regression. The ensemble method, which is straightforward
to implement, provides a very good sensitivity-specificity trade-off
for the highest and lowest rank.
Abstract: This paper presents Simulation and experimental
study aimed at investigating the effectiveness of an adaptive artificial
neural network stabilizer on enhancing the damping torque of a
synchronous generator. For this purpose, a power system comprising
a synchronous generator feeding a large power system through a
short tie line is considered. The proposed adaptive neuro-control
system consists of two multi-layered feed forward neural networks,
which work as a plant model identifier and a controller. It generates
supplementary control signals to be utilized by conventional
controllers. The details of the interfacing circuits, sensors and
transducers, which have been designed and built for use in tests, are
presented. The synchronous generator is tested to investigate the
effect of tuning a Power System Stabilizer (PSS) on its dynamic
stability. The obtained simulation and experimental results verify the
basic theoretical concepts.
Abstract: In the semiconductor manufacturing process, large
amounts of data are collected from various sensors of multiple
facilities. The collected data from sensors have several different characteristics
due to variables such as types of products, former processes
and recipes. In general, Statistical Quality Control (SQC) methods
assume the normality of the data to detect out-of-control states of
processes. Although the collected data have different characteristics,
using the data as inputs of SQC will increase variations of data,
require wide control limits, and decrease performance to detect outof-
control. Therefore, it is necessary to separate similar data groups
from mixed data for more accurate process control. In the paper,
we propose a regression tree using split algorithm based on Pearson
distribution to handle non-normal distribution in parametric method.
The regression tree finds similar properties of data from different
variables. The experiments using real semiconductor manufacturing
process data show improved performance in fault detecting ability.
Abstract: The present work was conducted for Arsenic (III)
removal, which one of the most poisonous groundwater pollutants, by
synthetic nano size zerovalent iron (nZVI). Batch experiments were
performed to investigate the influence of As (III), nZVI
concentration, pH of solution and contact time on the efficiency of As
(III) removal. nZVI was synthesized by reduction of ferric chloride
by sodium borohydrid. SEM and XRD were used to determine
particle size and characterization of produced nanoparticles. Up to
99.9% removal efficiency for arsenic (III) was obtained by nZVI
dosage of 1 g/L at time equal to 10 min. and pH=7. It could be
concluded that the removal efficiency were enhanced with increasing
of ZVI dosage and reaction time, but decreased with increasing of
arsenic concentration and pH for nano sized ZVI. nZVI presented an
outstanding ability to remove As (III) due to not only a high surface
area and low particle size but also to high inherent activity.
Abstract: In this paper, the problem of reducing switching
activity in on-chip buses at the stage of high-level synthesis is
considered, and a high-level low power bus binding based on dynamic
bit reordering is proposed. Whereas conventional methods use a fixed
bit ordering between variables within a bus, the proposed method
switches a bit ordering dynamically to obtain a switching activity
reduction. As a result, the proposed method finds a binding solution
with a smaller value of total switching activity (TSA). Experimental
result shows that the proposed method obtains a binding solution
having 12.0-34.9% smaller TSA compared with the conventional
methods.
Abstract: Accurate loss minimization is the critical component
for efficient electrical distribution power flow .The contribution of
this work presents loss minimization in power distribution system
through feeder restructuring, incorporating DG and placement of
capacitor. The study of this work was conducted on IEEE
distribution network and India Electricity Board benchmark
distribution system. The executed experimental result of Indian
system is recommended to board and implement practically for
regulated stable output.
Abstract: This paper presents a wrap-around view system with 4
smart cameras module and remote motion mobile robot control equipped with smart camera module system. The two-level scheme for
remote motion control with smart-pad(IPAD) is introduced on this
paper. In the low-level, the wrap-around view system is controlled or operated to keep the reference points lying around top view image
plane. On the higher level, a robot image based motion controller is utilized to drive the mobile platform to reach the desired position or
track the desired motion planning through image feature feedback. The
design wrap-around view system equipped on presents such advantages as follows: 1) a satisfactory solution for the FOV and affine
problem; 2) free of any complex and constraint with robot pose. The performance of the wrap-around view equipped on mobile robot
remote control is proven by experimental results.
Abstract: Due to the environmental and price issues of current
energy crisis, scientists and technologists around the globe are
intensively searching for new environmentally less-impact form of
clean energy that will reduce the high dependency on fossil fuel.
Particularly hydrogen can be produced from biomass via thermochemical
processes including pyrolysis and gasification due to the
economic advantage and can be further enhanced through in-situ
carbon dioxide removal using calcium oxide. This work focuses on
the synthesis and development of the flowsheet for the enhanced
biomass gasification process in PETRONAS-s iCON process
simulation software. This hydrogen prediction model is conducted at
operating temperature between 600 to 1000oC at atmospheric
pressure. Effects of temperature, steam-to-biomass ratio and
adsorbent-to-biomass ratio were studied and 0.85 mol fraction of
hydrogen is predicted in the product gas. Comparisons of the results
are also made with experimental data from literature. The
preliminary economic potential of developed system is RM 12.57 x
106 which equivalent to USD 3.77 x 106 annually shows economic
viability of this process.
Abstract: A new algorithm called Character-Comparison to Character-Access (CCCA) is developed to test the effect of both: 1) converting character-comparison and number-comparison into character-access and 2) the starting point of checking on the performance of the checking operation in string searching. An experiment is performed using both English text and DNA text with different sizes. The results are compared with five algorithms, namely, Naive, BM, Inf_Suf_Pref, Raita, and Cycle. With the CCCA algorithm, the results suggest that the evaluation criteria of the average number of total comparisons are improved up to 35%. Furthermore, the results suggest that the clock time required by the other algorithms is improved in range from 22.13% to 42.33% by the new CCCA algorithm.
Abstract: Fixed-bed slow pyrolysis experiments of rice husk
have been conducted to determine the effect of pyrolysis
temperature, heating rate, particle size and reactor length on the
pyrolysis product yields. Pyrolysis experiments were performed at
pyrolysis temperature between 400 and 600°C with a constant
heating rate of 60°C/min and particle sizes of 0.60-1.18 mm. The
optimum process conditions for maximum liquid yield from the rice
husk pyrolysis in a fixed bed reactor were also identified. The highest
liquid yield was obtained at a pyrolysis temperature of 500°C,
particle size of
1.18-1.80 mm, with a heating rate of 60°C/min in a 300 mm length
reactor. The obtained yield of, liquid, gas and solid were found be in
the range of 22.57-31.78 %, 27.75-42.26 % and 34.17-42.52 % (all
weight basics) respectively at different pyrolysis conditions. The
results indicate that the effects of pyrolysis temperature and particle
size on the pyrolysis yield are more significant than that of heating
rate and reactor length. The functional groups and chemical
compositions present in the liquid obtained at optimum conditions
were identified by Fourier Transform-Infrared (FT-IR) spectroscopy
and Gas Chromatography/ Mass Spectroscopy (GC/MS) analysis
respectively.