Abstract: Analyse of locally manufactured Low Density Polyethylene (LDPE) durability, used within lining systems at bottom of Municipal Solid Waste (landfill), is done in the present work. For this end, short and middle time creep behavior under tension of the analyzed material is carried out. The locally manufactured material is tested and compared to the European one (LDPE-CE). Both materials was tested in 03 various mediums: ambient and two aggressive (salty water and foam water), using three specimens in each case. A testing campaign is carried out using an especially designed and achieved testing bench. Moreover, characterisation tests were carried out to evaluate the medium effect on the mechanical properties of the tested material (LDPE). Furthermore, experimental results have been used to establish a law regression which can be used to predict creep behaviour of the analyzed material. As a result, the analyzed LDPE material has showed a good stability in different ambient and aggressive mediums; as well, locally manufactured LDPE seems more flexible, compared with the European one. This makes it more useful to the desired application.
Abstract: In this paper a multi-objective nonlinear programming
model of cellular manufacturing system is presented which minimize
the intercell movements and maximize the sum of reliability of cells.
We present a genetic approach for finding efficient solutions to the
problem of cell formation for products having multiple routings.
These methods find the non-dominated solutions and according to
decision makers prefer, the best solution will be chosen.
Abstract: Mining Sequential Patterns in large databases has become
an important data mining task with broad applications. It is
an important task in data mining field, which describes potential
sequenced relationships among items in a database. There are many
different algorithms introduced for this task. Conventional algorithms
can find the exact optimal Sequential Pattern rule but it takes a
long time, particularly when they are applied on large databases.
Nowadays, some evolutionary algorithms, such as Particle Swarm
Optimization and Genetic Algorithm, were proposed and have been
applied to solve this problem. This paper will introduce a new kind
of hybrid evolutionary algorithm that combines Genetic Algorithm
(GA) with Particle Swarm Optimization (PSO) to mine Sequential
Pattern, in order to improve the speed of evolutionary algorithms
convergence. This algorithm is referred to as SP-GAPSO.
Abstract: Schema matching plays a key role in many different
applications, such as schema integration, data integration, data
warehousing, data transformation, E-commerce, peer-to-peer data
management, ontology matching and integration, semantic Web,
semantic query processing, etc. Manual matching is expensive and
error-prone, so it is therefore important to develop techniques to
automate the schema matching process. In this paper, we present a
solution for XML schema automated matching problem which
produces semantic mappings between corresponding schema
elements of given source and target schemas. This solution
contributed in solving more comprehensively and efficiently XML
schema automated matching problem. Our solution based on
combining linguistic similarity, data type compatibility and structural
similarity of XML schema elements. After describing our solution,
we present experimental results that demonstrate the effectiveness of
this approach.
Abstract: Urinary Tract Infections (UTI) account for an estimated 25-40% nosocomial infection, out of which 90% are associated with urinary catheter, called Catheter associated urinary tract infection (CAUTI). The microbial populations within CAUTI frequently develop as biofilms. In the present study, microbial contamination of indwelling urinary catheters was investigated. Biofilm forming ability of the isolates was determined by tissue culture plate method. Prevention of biofilm formation in the urinary catheter by Pseudomonas aeruginosa was also determined by coating the catheter with some enzymes, gentamycin and EDTA. It was found that 64% of the urinary catheters get contaminated during the course of catheterization. Of the total 6 isolates, biofilm formation was seen in 100% Pseudomonas aeruginosa and E. coli, 90% in Enterococci, 80% in Klebsiella and 66% in S. aureus. It was noted that the biofilm production by Pseudomonas was prolonged by 7 days in amylase, 8 days in protease, 6 days in lysozyme, 7days in gentamycin and 5 days in EDTA treated catheter.
Abstract: Grid computing is growing rapidly in the distributed
heterogeneous systems for utilizing and sharing large-scale resources
to solve complex scientific problems. Scheduling is the most recent
topic used to achieve high performance in grid environments. It aims
to find a suitable allocation of resources for each job. A typical
problem which arises during this task is the decision of scheduling. It
is about an effective utilization of processor to minimize tardiness
time of a job, when it is being scheduled. This paper, therefore,
addresses the problem by developing a general framework of grid
scheduling using dynamic information and an ant colony
optimization algorithm to improve the decision of scheduling. The
performance of various dispatching rules such as First Come First
Served (FCFS), Earliest Due Date (EDD), Earliest Release Date
(ERD), and an Ant Colony Optimization (ACO) are compared.
Moreover, the benefit of using an Ant Colony Optimization for
performance improvement of the grid Scheduling is also discussed. It
is found that the scheduling system using an Ant Colony
Optimization algorithm can efficiently and effectively allocate jobs
to proper resources.
Abstract: Distance protection of transmission lines including advanced flexible AC transmission system (FACTS) devices has been a very challenging task. FACTS devices of interest in this paper are static synchronous series compensators (SSSC) and unified power flow controller (UPFC). In this paper, a new algorithm is proposed to detect and classify the fault and identify the fault position in a transmission line with respect to a FACTS device placed in the midpoint of the transmission line. Discrete wavelet transformation and wavelet entropy calculations are used to analyze during fault current and voltage signals of the compensated transmission line. The proposed algorithm is very simple and accurate in fault detection and classification. A variety of fault cases and simulation results are introduced to show the effectiveness of such algorithm.
Abstract: The effects of equilibrium time, solution pH, and
sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied
using a batch equilibration method. UV–VIS spectroscopy was used
to obtain the adsorption isotherms at 20° C. The optimum period for
adsorption was 300 min. However, MB removal increased from
81,82 % to 94,81 %. The equilibrium adsorption data was analyzed
by using Langmuir, Freundlich and Temkin isotherm models.
Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed
that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors
from aqueous solutions.
Abstract: Extraction of edge-end-pixels is an important step for the edge linking process to achieve edge-based image segmentation. This paper presents an algorithm to extract edge-end pixels together with their directional sensitivities as an augmentation to the currently available mathematical models. The algorithm is implemented in the Java environment because of its inherent compatibility with web interfaces since its main use is envisaged to be for remote image analysis on a virtual instrumentation platform.
Abstract: Multi User Virtual Worlds are becoming a valuable educational tool. Learning experiences within these worlds focus on discovery and active experiences that both engage students and motivate them to explore new concepts. As educators, we need to explore these environments to determine how they can most effectively be used in our instructional practices. This paper explores the current application of virtual worlds to identify meaningful educational strategies that are being used to engage students and enhance teaching and learning.
Abstract: In the present work, a study has been made on the combination of the electrical discharge machining (EDM) with ultrasonic vibrations to improve the machining efficiency. In experiments the graphite used as tool electrode and material of workpiece was AISIH13 tool steel. The parameters such as discharge peak current and pulse duration were changed to explore their effect on the material removal rate (MRR), relative tool wear ratio (TWR) and surface roughness. From the experimental result it can be seen that ultrasonic vibration of the workpiece can significantly reduces the inactive pulses and improves the stability of process. It was found that ultrasonic assisted EDM (US-EDM) is effective in attaining a high material removal rate (MRR) in finishing regime.
Abstract: This paper considers the autonomous navigation
problem of multiple n-link nonholonomic mobile manipulators within
an obstacle-ridden environment. We present a set of nonlinear
acceleration controllers, derived from the Lyapunov-based control
scheme, which generates collision-free trajectories of the mobile
manipulators from initial configurations to final configurations in a
constrained environment cluttered with stationary solid objects of
different shapes and sizes. We demonstrate the efficiency of the
control scheme and the resulting acceleration controllers of the
mobile manipulators with results through computer simulations of an
interesting scenario.
Abstract: Detection, feature extraction and pose estimation of
people in images and video is made challenging by the variability of
human appearance, the complexity of natural scenes and the high
dimensionality of articulated body models and also the important
field in Image, Signal and Vision Computing in recent years. In this
paper, four types of people in 2D dimension image will be tested and
proposed. The system will extract the size and the advantage of them
(such as: tall fat, short fat, tall thin and short thin) from image. Fat
and thin, according to their result from the human body that has been
extract from image, will be obtained. Also the system extract every
size of human body such as length, width and shown them in output.
Abstract: Un-doped GaN film of thickness 1.90 mm, grown on
sapphire substrate were uniformly implanted with 325 keV Mn+ ions
for various fluences varying from 1.75 x 1015 - 2.0 x 1016 ions cm-2 at
3500 C substrate temperature. The structural, morphological and
magnetic properties of Mn ion implanted gallium nitride samples
were studied using XRD, AFM and SQUID techniques. XRD of the
sample implanted with various ion fluences showed the presence of
different magnetic phases of Ga3Mn, Ga0.6Mn0.4 and Mn4N.
However, the compositions of these phases were found to be
depended on the ion fluence. AFM images of non-implanted sample
showed micrograph with rms surface roughness 2.17 nm. Whereas
samples implanted with the various fluences showed the presence of
nano clusters on the surface of GaN. The shape, size and density of
the clusters were found to vary with respect to ion fluence. Magnetic
moment versus applied field curves of the samples implanted with
various fluences exhibit the hysteresis loops. The Curie temperature
estimated from zero field cooled and field cooled curves for the
samples implanted with the fluence of 1.75 x 1015, 1.5 x 1016 and 2.0
x 1016 ions cm-2 was found to be 309 K, 342 K and 350 K
respectively.
Abstract: A neurofuzzy approach for a given set of input-output training data is proposed in two phases. Firstly, the data set is partitioned automatically into a set of clusters. Then a fuzzy if-then rule is extracted from each cluster to form a fuzzy rule base. Secondly, a fuzzy neural network is constructed accordingly and parameters are tuned to increase the precision of the fuzzy rule base. This network is able to learn and optimize the rule base of a Sugeno like Fuzzy inference system using Hybrid learning algorithm, which combines gradient descent, and least mean square algorithm. This proposed neurofuzzy system has the advantage of determining the number of rules automatically and also reduce the number of rules, decrease computational time, learns faster and consumes less memory. The authors also investigate that how neurofuzzy techniques can be applied in the area of control theory to design a fuzzy controller for linear and nonlinear dynamic systems modelling from a set of input/output data. The simulation analysis on a wide range of processes, to identify nonlinear components on-linely in a control system and a benchmark problem involving the prediction of a chaotic time series is carried out. Furthermore, the well-known examples of linear and nonlinear systems are also simulated under the Matlab/Simulink environment. The above combination is also illustrated in modeling the relationship between automobile trips and demographic factors.
Abstract: There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..
Abstract: A numerical study is presented on buckling and post
buckling behaviour of laminated carbon fiber reinforced plastic
(CFRP) thin-walled cylindrical shells under axial compression using
asymmetric meshing technique (AMT). Asymmetric meshing
technique is a perturbation technique to introduce disturbance without
changing geometry, boundary conditions or loading conditions.
Asymmetric meshing affects predicted buckling load, buckling mode
shape and post-buckling behaviour. Linear (eigenvalue) and nonlinear
(Riks) analyses have been performed to study the effect of
asymmetric meshing in the form of a patch on buckling behaviour.
The reduction in the buckling load using Asymmetric meshing
technique was observed to be about 15%. An isolated dimple formed
near the bifurcation point and the size of which increased to reach a
stable state in the post-buckling region. The load-displacement curve
behaviour applying asymmetric meshing is quite similar to the curve
obtained using initial geometric imperfection in the shell model.
Abstract: Few decades ago, electronic and sensor technologies
are merged into vehicles as the Advanced Driver Assistance
System(ADAS). However, sensor-based ADASs have limitations
about weather interference and a line-of-sight nature problem. In our
project, we investigate a Relative Position based ADAS(RP-ADAS).
We divide the RP-ADAS into four main research areas: GNSS,
VANET, Security/Privacy, and Application. In this paper, we research
the GNSS technologies and determine the most appropriate one. With
the performance evaluation, we figure out that the C/A code based
GPS technologies are inappropriate for 'which lane-level' application.
However, they can be used as a 'which road-level' application.
Abstract: There are only limited studies that directly correlate
the increase in reinforced concrete (RC) panel structural capacities in
resisting the blast loads with different RC panel structural properties
in terms of blast loading characteristics, RC panel dimensions, steel
reinforcement ratio and concrete material strength. In this paper,
numerical analyses of dynamic response and damage of the one-way
RC panel to blast loads are carried out using the commercial software
LS-DYNA. A series of simulations are performed to predict the blast
response and damage of columns with different level and magnitude
of blast loads. The numerical results are used to develop pressureimpulse
(P-I) diagrams of one-way RC panels. Based on the
numerical results, the empirical formulae are derived to calculate the
pressure and impulse asymptotes of the P-I diagrams of RC panels.
The results presented in this paper can be used to construct P-I
diagrams of RC panels with different concrete and reinforcement
properties. The P-I diagrams are very useful to assess panel capacities
in resisting different blast loads.
Abstract: Type 2 diabetes mellitus (T2DM) is a complex
metabolic disorder that characterized by the presence of high glucose
in blood that cause from insulin resistance and insufficiency due to
deterioration β-cell Langerhans functions. T2DM is commonly
caused by the combination of inherited genetic variations as well as
our own lifestyle. Metallothionein (MT) is a known cysteine-rich
protein responsible in helping zinc homeostasis which is important in
insulin signaling and secretion as well as protection our body from
reactive oxygen species (ROS). MT scavenged ROS and free
radicals in our body happen to be one of the reasons of T2DM and its
complications. The objective of this study was to investigate the
association of MT1A and MT2A polymorphisms between T2DM and
control subjects among Malay populations. This study involved 150
T2DM and 120 Healthy individuals of Malay ethnic with mixed
genders. The genomic DNA was extracted from buccal cells and
amplified for MT1A and MT2A loci; the 347bp and 238bp banding
patterns were respectively produced by mean of the Polymerase
Chain Reaction (PCR). The PCR products were digested with Mlucl
and Tsp451 restriction enzymes respectively and producing
fragments lengths of (158/189/347bp) and (103/135/238bp)
respectively. The ANOVA test was conducted and it shown that there
was a significant difference between diabetic and control subjects for
age, BMI, WHR, SBP, FPG, HBA1C, LDL, TG, TC and family
history with (P0.05). The genotype
frequency for AA, AG and GG of MT1A polymorphisms was 72.7%,
22.7% and 4.7% in cases and 15%, 55% and 30% in control
respectively. As for MT2A, genotype frequency of GG, GC and CC
was 42.7%, 27.3% and 30% in case and 5%, 40% and 55% for
control respectively. Both polymorphisms show significant difference
between two investigated groups with (P=0.000). The Post hoc test
was conducted and shows a significant difference between the
genotypes within each polymorphism (P=0. 000). The MT1A and
MT2A polymorphisms were believed to be the reliable molecular
markers to distinguish the T2DM subjects from healthy individuals in
Malay populations.